50+ Google Cloud Platform (GCP) Jobs in Bangalore (Bengaluru) | Google Cloud Platform (GCP) Job openings in Bangalore (Bengaluru)

Role & Responsibilities

• Develop and deliver automation software to build and improve platform functionality
• Ensure reliability, availability, and manageability of applications and cloud platforms
• Champion adoption of Infrastructure as Code (IaC) practices
• Design and build self-service, self-healing, monitoring, and alerting platforms
• Automate development and testing workflows through CI/CD pipelines (Git, Jenkins, SonarQube, Artifactory, Docker containers)
• Build and manage container hosting platforms using Kubernetes

Requirements

• Strong experience deploying and maintaining GCP cloud infrastructure
• Well-versed in service-oriented and cloud-based architecture design patterns
• Knowledge of cloud services including compute, storage, networking, messaging, and automation tools (e.g., CloudFormation/Terraform equivalents)
• Experience with relational and NoSQL databases (Postgres, Cassandra)
• Hands-on experience with automation/configuration tools (Puppet, Chef, Ansible, Terraform)

Additional Skills

• Strong Linux system administration and troubleshooting skills
• Programming/scripting exposure (Bash, Python, Core Java, or Scala)
• CI/CD pipeline experience (Jenkins, Git, Maven, etc.)
• Experience integrating solutions in multi-region environments
• Familiarity with Agile/Scrum/DevOps methodologies

Experience

• 5+ years of experience in building and managing Data Lakes, Data Warehouses, Data Integration, Data Migration, and Business Intelligence/Artificial Intelligence solutions on GCP, AWS, or Azure.
• Experience leading end-to-end cloud data engineering and migration projects.

Solution Design & Architecture

• Understand business requirements and translate them into functional and non-functional requirements.
• Design scalable, secure, high-performance, and resilient data platforms.
• Architect and implement end-to-end data pipelines for structured and unstructured data.
• Design distributed, batch, real-time, and event-driven data processing systems.
• Lead cloud migration initiatives from on-premises to GCP, AWS, or Azure.

Data Engineering & Big Data

• Hands-on experience with:
• Spark, PySpark, Scala
• Dataflow, Dataproc, EMR
• Hadoop ecosystem
• Expertise in ETL/ELT and data integration using:
• Informatica
• DataStage
• Talend
• OWB

Databases & Data Warehousing

• Experience with cloud and on-premises databases:
• BigQuery, Redshift
• Cloud SQL, Cloud Spanner, Bigtable
• RDS, Aurora, DynamoDB
• Oracle, Teradata, MySQL, DB2, SQL Server
• Exposure to NoSQL databases:
• MongoDB
• Cassandra
• CouchDB
• GraphDB

Data Pipeline & Integration Tools

Experience with one or more of:

• S3 / Cloud Storage
• Athena
• AWS Glue
• Sqoop
• Flume
• Hive
• Kafka
• Google Pub/Sub
• Amazon Kinesis
• Airflow / Cloud Composer
• Spark SQL
• Presto
• EMRFS

Cloud & Platform Knowledge

• Strong understanding of:
• GCP, AWS, and Azure services
• IaaS, PaaS, SaaS
• Containers & Microservices
• Cloud Security & Governance
• Ability to compare cloud-native services and recommend the best-fit architecture.

Business Intelligence & Machine Learning

• Experience with BI tools:
• Looker
• Tableau
• Power BI
• SAP BO
• Cognos
• Superset
• Good to have exposure to:
• TensorFlow
• PyTorch

Key Responsibilities

• Lead multiple cloud data engineering engagements across Data Lakes, Data Warehousing, Data Migration, and BI solutions.
• Work closely with business and technology stakeholders to gather requirements and define technical solutions.
• Own end-to-end project delivery, ensuring quality, timelines, and customer satisfaction.
• Build scalable, high-volume, batch and streaming data processing systems.
• Establish data validation, monitoring, and quality assurance processes.
• Ensure production data is reliable, accurate, and readily available for business users.
• Support pre-sales activities, including RFPs, RFIs, and solution design.
• Mentor junior engineers and drive technical excellence within the team.
• Contribute to reusable frameworks, accelerators, and best practices.

We're looking for a Senior Data Modeler to lead the design and evolution of our enterprise data warehouse, with a primary focus on transforming Guidewire (PolicyCenter, BillingCenter, ClaimCenter) and other insurance source system data into well-architected, analytics-ready models on Google BigQuery. This is a hands-on, high-autonomy role for someone who can own modeling decisions end-to-end — from source system analysis through to production-grade dimensional or Data Vault structures — with minimal oversight.

You'll work across multiple insurance lines of business (Property, Casualty, Financial Lines, Specialty) and partner closely with engineering, BI, and business stakeholders to ensure the data model is technically sound and supports reporting, actuarial, and analytics use cases.

Responsibilities:

• Design and own enterprise-scale data models across multiple insurance domains.
• Translate complex Guidewire schemas (PolicyCenter, BillingCenter, ClaimCenter) into governed warehouse structures.
• Apply appropriate modeling techniques including:
• Dimensional Modeling (Star/Snowflake)
• 3NF/Normalized Modeling
• Data Vault 2.0 (Hubs, Links, Satellites)
• Hybrid and Denormalized Models
• Model effective-dated and slowly changing insurance data, including policy versioning, endorsements, premium earning, and claims history.
• Design conformed dimensions and fact tables supporting Premium, Claims, and Billing reporting.
• Optimize BigQuery performance through partitioning, clustering, materialized views, query tuning, and cost-efficient schema design.
• Create and maintain ERDs, source-to-target mappings, data dictionaries, and lineage documentation.
• Collaborate with Data Engineers to ensure physical implementation aligns with logical models.
• Establish modeling standards and mentor team members through hands-on leadership.
• Independently drive solutions from ambiguous business requirements.
• Communicate modeling decisions and trade-offs to both technical and business stakeholders.

Required Skills & Experience:

• 7+ years of enterprise-scale Data Modeling experience.
• Strong Insurance domain expertise, preferably with Guidewire:
• PolicyCenter
• BillingCenter
• ClaimCenter
• Experience with alternative insurance platforms such as Duck Creek or Sapiens is also valuable.
• Deep expertise in:
• Dimensional Modeling (Kimball)
• 3NF Data Modeling
• Data Vault 2.0
• Denormalized Data Warehousing
• Strong BigQuery knowledge:
• Partitioning & Clustering
• Query Performance Optimization
• Cost-Aware Schema Design
• Expertise in modeling effective-dated and temporal data.
• Excellent communication and stakeholder management skills.
• Proven ability to lead through hands-on technical contributions.
• Ability to work independently with minimal supervision.

Nice to Have:

• Insurance premium calculations and reconciliation:
• Earned / Unearned / Written Premium
• GWP Reconciliation
• Premium Earning Schedules
• Knowledge of Guidewire data model patterns:
• Effective Dating
• FixedID / BranchID
• CDA / ODS Layers
• Experience with Data Vault automation tools.
• Exposure to Snowflake or Redshift.
• Experience mentoring Data Modelers and Data Engineers.

What Success Looks Like:

• Well-documented, scalable enterprise data models.
• Cost-efficient, high-performance modeling decisions.
• Improved modeling maturity across the team.
• Strong stakeholder confidence in the data architecture and design decisions.

We are looking for an experienced BI Solution Architect to lead the design and implementation of scalable, secure, and high-performing Data & BI platforms across Azure and GCP environments.

This role will own the end-to-end data architecture covering ingestion, storage, processing, transformation, analytics, and visualization while driving enterprise BI strategy, reporting governance, and modernization initiatives. The ideal candidate will work closely with business stakeholders, enterprise architects, and engineering teams to deliver robust, production-ready analytics solutions.

Key Responsibilities:

Data Architecture & Solution Design

• Define architecture for data ingestion, storage, processing, and transformation across Azure and GCP.
• Design scalable, resilient, and enterprise-grade data platforms aligned with architectural standards.
• Create data models, architecture blueprints, and end-to-end data flow designs.
• Collaborate with enterprise architects to ensure architectural compliance and governance.

Data Platform & Pipeline Architecture

• Design and oversee large-scale distributed data platforms and pipelines.
• Define standards for data ingestion, transformation, and consumption layers.
• Enable development of scalable and reusable data products.
• Promote modern data architectures including:
• Data Lake
• Lakehouse
• Data Mesh

BI Strategy & Architecture

• Define and drive enterprise BI strategy aligned with business objectives.
• Standardize BI architecture and reporting frameworks across the organization.
• Evaluate and recommend BI technologies including:
• Power BI
• Tableau
• SAP Business Objects (BO)
• Develop reusable blueprints, patterns, and accelerators.
• Lead proof-of-concepts (POCs) and BI modernization initiatives.

Visualization Governance

• Establish dashboard development standards and visualization best practices.
• Define governance frameworks to improve dashboard quality, consistency, and usability.
• Review dashboards prior to production deployment.
• Guide teams in creating intuitive, business-focused, and high-performance visualizations.

Data Governance & Enterprise Data Management

• Define and enforce enterprise data governance standards.
• Drive metadata management, master data management, and reference data practices.
• Establish data quality frameworks, validation mechanisms, and monitoring processes.
• Create technical glossaries and enterprise-wide data standards.

Security & Compliance

• Define access management and security standards across Data & BI platforms.
• Implement controls for sensitive and regulated data.
• Ensure compliance with enterprise policies and regulatory requirements.

Performance & Optimization

• Define monitoring, tuning, and optimization strategies for data pipelines and dashboards.
• Ensure scalability, responsiveness, and reliability of analytics platforms.
• Implement proactive monitoring and observability frameworks.

Leadership & Stakeholder Management

• Partner with Product Owners, Business Analysts, and stakeholders to translate requirements into architecture solutions.
• Collaborate with Data Engineers, Analysts, and Data Scientists to solve complex technical challenges.
• Mentor engineers and associate architects.
• Lead architecture reviews and drive solution governance.

Data Lifecycle & Operations

• Own end-to-end data lifecycle management:
• Ingestion
• Processing
• Storage
• Archival
• Ensure operational readiness and reliability of critical data platforms.
• Drive best practices around scalability, resilience, and sustainability.

Migration & Modernization

• Lead Tableau-to-Power BI migration strategy and execution.
• Design dual-platform architectures to ensure business continuity during migration.
• Drive legacy platform rationalization and modernization initiatives.
• Optimize infrastructure and licensing costs while reducing total cost of ownership (TCO).

Required Qualifications

Experience

• 8+ years of experience in Data Engineering, Big Data, Analytics, or Data Architecture.
• Proven experience designing enterprise-scale data platforms and analytics solutions.
• Strong stakeholder management and leadership experience.

Technical Expertise

• Strong expertise in Azure and GCP data ecosystems.
• Deep understanding of:
• Data Modeling
• ETL / ELT
• Distributed Systems
• Enterprise Data Platforms
• Experience with modern architectures:
• Data Lake
• Lakehouse
• Data Mesh

BI & Analytics

• Strong hands-on experience with:
• Power BI
• Tableau
• SAP Business Objects (BO)
• Expertise in:
• BI Architecture
• Dashboard Design
• Visualization Best Practices
• Reporting Governance

Data Governance

• Strong understanding of:
• Data Governance
• Data Quality
• Metadata Management
• Data Lifecycle Management

Must-Have Skills

• Data Architecture & Solution Design (Azure & GCP)
• Large-Scale Data Platform & Pipeline Design
• Data Modeling & ETL/ELT Architecture
• Distributed Systems
• Data Lake / Lakehouse / Data Mesh
• Power BI & Tableau
• Data Governance & Data Quality
• Enterprise BI Architecture
• Stakeholder Management & Leadership

Good-to-Have Skills

• Enterprise Data Platforms & Multi-Cloud Environments
• CI/CD Pipelines & Automation for Data & BI Platforms
• Real-Time / Streaming Data Architectures
• BI Transformation & Modernization Programs
• Tableau to Power BI Migration Experience
• Azure Data Engineer / Architect Certifications
• GCP Professional Data Engineer / Cloud Architect Certifications

Why Join Us?

• Lead architecture for enterprise-scale Data & BI platforms.
• Drive organization-wide data and analytics strategy.
• Work on modern cloud ecosystems across Azure and GCP.
• High ownership, visibility, and stakeholder exposure.
• Opportunity to shape long-term data, analytics, and visualization roadmaps.

Key Responsibilities

1. Target State Design

• Design and implement a scalable, secure, and domain-driven Data Lakehouse architecture on GCP.
• Define enterprise-grade data architecture standards and reference frameworks.

2. Migration Leadership

• Lead end-to-end migration from legacy platforms (Exasol, Lua, Control-M) to GCP BigQuery and Dataform.
• Drive migration planning, execution, validation, and optimization.

3. Data Modeling

• Design conceptual, logical, and physical data models.
• Implement:
• Data Vault 2.0 (Silver Layer)
• Dimensional Modeling (Gold Layer)

4. Framework Development

• Build reusable, configuration-driven data pipeline frameworks.
• Establish best practices for scalable and accelerated development.

5. Governance & Security

• Implement enterprise data governance using:
• Dataplex
• Data Catalog
• Analytics Hub
• Enable data lineage, cataloging, automated data quality checks, and PII masking using DLP.

6. Orchestration & Automation

• Architect workflows using Cloud Composer (Airflow).
• Automate infrastructure provisioning through Terraform (IaC).

7. BI Modernization

• Reconfigure and validate:
• ~1,000 Tableau & Power BI dashboards
• ~250 semantic/data models
• Ensure successful migration to BigQuery curated layers.

8. Stakeholder Management

• Partner with Engineering Leads, Architects, and Business Teams.
• Translate business requirements into Technical Design Documents (TDDs).
• Drive architecture reviews and approvals.

9. Quality Assurance

• Conduct code reviews and enforce enterprise standards.
• Support UAT and automated validation using QuerySurge.

10. Team Leadership

• Mentor data engineering teams.
• Conduct technical enablement sessions and knowledge transfer workshops.

Required Skills & Experience

Data Engineering & Database Expertise

• Strong expertise in BigQuery architecture, optimization, and stored procedures.
• Advanced SQL programming skills.
• Experience modernizing legacy ETL (Lua-based) into modern ELT frameworks.
• Strong understanding of:
• Data Vault 2.0
• Dimensional Modeling
• Experience with Exasol or similar legacy data warehouses is highly preferred.

GCP & Modern Data Stack

• Hands-on experience with:
• BigQuery
• Dataform (Mandatory)
• Cloud Composer (Airflow)
• Dataflow
• GCS
• Deep expertise in:
• Dataplex
• Data Catalog
• Analytics Hub

Security & Governance

• Experience implementing:
• IAM Roles & Policies
• Cloud KMS
• DLP API
• Strong understanding of enterprise governance and compliance frameworks.

Architecture & DevOps

• Enterprise Data Architecture design experience.
• Cost estimation, sizing, and capacity planning on GCP.
• CI/CD implementation and Terraform-based infrastructure automation.

Soft Skills

• Strong stakeholder management and communication skills.
• Experience leading discovery and solution design workshops.
• Ability to lead distributed Agile/Scrum teams.
• Excellent technical documentation skills (TDD/TSD creation).

Must-Have Skills

• 10+ years of Data Engineering / Data Architecture experience.
• Expertise in GCP BigQuery and Dataform.
• Hands-on experience with Data Vault 2.0.
• Experience implementing Dataplex for governance and security.
• Strong Terraform expertise.
• Proven experience migrating legacy warehouses such as:
• Exasol
• Teradata
• Netezza
• Similar enterprise DW platforms

Good-to-Have Skills

• Lua scripting experience.
• Control-M orchestration experience.
• Tableau and Power BI semantic/data model migration.
• QuerySurge for automated data validation.
• GCP Professional Data Engineer or Professional Cloud Architect certification.

Ideal Candidate Profile

• 10–15+ years of Data Engineering/Data Architecture experience.
• Led large-scale cloud modernization programs.
• Strong expertise in GCP Lakehouse architecture, governance, and migration frameworks.
• Comfortable working with enterprise stakeholders and leading cross-functional migration initiatives.

Minimum 8+ years of hands-on experience in Site Reliability Engineering (SRE) and/or DevOps.

Proven experience in a Technical Lead/Team Lead role.

Strong expertise in Linux administration and troubleshooting.

Hands-on experience with automation and scripting (Shell, Python, PowerShell, etc.).

Strong knowledge of DevOps tools and CI/CD pipelines.

Experience working on at least one major cloud platform: Azure, AWS, or GCP.

Experience managing production environments with a focus on availability, reliability, monitoring, and incident management.

Strong troubleshooting, problem-solving, and root cause analysis skills.

About Us

CLOUDSUFI, a Google Cloud Premier Partner, is a global leading provider of data-driven digital transformation across cloud-based enterprises. With a global presence and focus on Software & Platforms, Life sciences and Healthcare, Retail, CPG, financial services, and supply chain, CLOUDSUFI is positioned to meet customers where they are in their data monetization journey.

Our Values

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace. Please explore more at https://www.cloudsufi.com/

Summary

The Tech Lead is the technical spine of the engagement. They sit across all four delivery areas — Data Engineering, Frontend, ML/AI, and DevOps/Infrastructure — providing architectural direction, resolving cross-track dependencies, and ensuring the quality and coherence of everything we ship. Equally critical is the ability to represent CLOUDSUFI in a credible, articulate, and collaborative manner to Google counterparts at every level.

What You Will Do

Technical Leadership & Architecture

• Own the end-to-end technical architecture across all program tracks, ensuring alignment with Google Data Commons standards, APIs, and roadmap.

• Define and enforce engineering best practices, coding standards, and review processes across Data Engineering, Frontend, ML/AI, and DevOps/Infra workstreams.

• Make high-stakes design decisions on data modeling, pipeline architecture, schema design, and system integration — with clear documentation and traceability.

• Proactively identify technical risks, cross-track conflicts, and blockers; drive resolution before they impact delivery.

• Lead or participate in architecture review sessions with Google's core engineering team.

Cross-Track Coordination

• Act as the single technical point of contact horizontally across all tracks, breaking down silos and ensuring consistent patterns and interfaces.

• Facilitate technical syncs across track leads; surface dependencies early and coordinate sequencing of deliverables.

• Define shared standards for data contracts, API interfaces, and infrastructure configuration used across tracks.

Google Partnership & Communication

• Build and maintain a strong working relationship with the Google Data Commons core team — attending joint ceremonies, reviews, and design discussions.

• Represent CLOUDSUFI’s delivery quality and technical credibility in all interactions with Google stakeholders.

• Translate complex technical discussions into clear summaries for both technical and non-technical audiences across both organizations.

• Proactively communicate progress, blockers, and decisions to CLOUDSUFI leadership and Google program managers.

Delivery Quality & Engineering Excellence

• Drive code reviews, set quality gates, and ensure CI/CD pipelines, test coverage, and observability standards are met across all tracks.

• Champion performance, reliability, and scalability from design through production.

• Mentor and technically grow senior engineers across tracks without carrying formal HR responsibility.

• Contribute hands-on to critical technical work when needed — this is a hybrid IC and leadership role. Technology Stack & Domain Knowledge

Core / Must-Have

• Google Data Commons – deep familiarity with the Data Commons knowledge graph, DCID conventions, import pipelines, and the Statistical Variable hierarchy.

• Google Cloud Spanner – schema design, distributed transactions, interleaved tables, and performance tuning at scale.

• Google BigQuery – data modeling, partitioning/clustering strategies, query optimization, and integration with downstream consumers.

• Data pipelines – Apache Beam / Dataflow, or equivalent GCP-native ETL tooling.

• Infrastructure as Code – Terraform on GCP; Cloud Build, Artifact Registry, GKE or Cloud Run.

Strong Advantage

• Python (primary language for Data Commons import tooling and ML pipelines).

• TypeScript / React for the Data Commons web frontend and visualization layers.

• Vertex AI, BigQuery ML, or equivalent ML lifecycle tooling.

• Knowledge graph principles, RDF/SPARQL, or statistical data modeling.

• Data Commons Python / REST APIs and the DCID import automation tools.

• Experience with Google's internal engineering culture, tools (e.g. Buganizer, Critique, Cider), or prior delivery inside a Google product or partnership engagement.

Experience & Qualifications Required

• 10+ years of software engineering experience, with at least 3 years in a formal or informal tech lead capacity overseeing multiple workstreams.

• Demonstrable experience delivering production-grade systems on Google Cloud Platform.

• Prior experience working with or for Google — as a Googler, through a Google partnership program, or as a contractor embedded in a Google team — is strongly preferred.

• Exceptional verbal and written English communication skills; able to engage confidently with senior Google engineers and program managers.

• Proven ability to operate across ambiguous, fast-moving programs with multiple parallel tracks.

• Based in Bangalore, India, and able to work on-site at Google's Bangalore office on a regular basis.

Preferred

• Experience in the data and AI consulting or professional services space, particularly within the Google Cloud partner ecosystem.

• Familiarity with open data, public statistics, or knowledge graph use cases (e.g. UN SDG data, census data, health/economic indicators).

• Prior contribution to open-source projects, particularly Google Data Commons or related tooling.

What CLOUDSUFI Offers

• A flagship engagement at the intersection of Google's open data infrastructure and real-world AI/data impact.

• Daily collaboration with Google's core engineering team — a rare opportunity to work inside one of Google's strategic open data initiatives.

• Competitive compensation benchmarked at Staff / Principal level in the Bangalore market.

• CLOUDSUFI’s full benefits package.

• A culture that values technical excellence, client trust, and a people-first approach to delivery.

Job Summary

We are seeking an experienced BI Developer with strong expertise in Power BI/Tableau and Azure to support large-scale business intelligence initiatives, including report development, dashboarding, and platform transformation.

The ideal candidate will have a strong focus on data visualization, storytelling, and analytics delivery, along with experience in BI platform management and migration. You will play a key role in designing intuitive, high-impact dashboards and ensuring business users have actionable insights readily available.

Key Responsibilities

BI Development, Visualization and Dashboarding

• Design and implement reports, interactive dashboards, and data models using BI tools to enable data-driven decision-making
• Work with Data Product Owners and stakeholders to understand analytical goals and translate them into impactful dashboards
• Develop intuitive, visually compelling dashboards with a strong focus on usability and storytelling
• Identify and rapidly resolve issues related to data visualization, performance, and user experience
• Ensure consistency, standardization, and reusability across dashboards and reporting layers

BI Migration and Transformation

• Lead or support migration of reports and dashboards across BI platforms (e.g., Tableau to Power BI)
• Translate existing reports into optimized, scalable Power BI solutions
• Improve reporting frameworks during migration for better performance and usability

Data Modeling and Integration

• • Develop robust data models using Power BI (DAX, Power Query) or equivalent tools
• • Work closely with data engineers, analysts, and scientists to build reliable datasets for reporting
• • Validate and optimize data pipelines feeding BI systems
• • Ensure data accuracy, consistency, and governance across reporting solutions

Collaboration and Cross-Functional Delivery

• Collaborate closely with data engineers, data analysts, and data scientists to deliver end-to-end analytics solutions
• Work with business stakeholders to refine requirements and improve reporting outcomes
• Contribute to building scalable and reusable reporting frameworks

BI Platform Administration and Management

• Administer BI platforms such as Power BI, Tableau, or SAP BO
• Manage workspaces, access control, tenant settings, and user permissions
• Handle capacity planning, cost optimization, and resource utilization
• Perform regular housekeeping and monitor usage to optimize platform efficiency

Platform Maintenance and Reliability

Ensure platform performance, scalability, security, compliance, and uptime

Plan and execute platform maintenance, including patching and release management

Support platform “evergreening” and manage audit logs for troubleshooting

Infrastructure, Deployment and Monitoring

• Support installation, configuration, and setup of BI tools and environments
• Design and implement deployment architecture for BI solutions
• Build automated health checks, monitoring, and alerting mechanisms
• Integrate monitoring with enterprise systems (e.g., NOC) and ensure support readiness

Governance and Quality

• Ensure data and reporting governance across dashboards and BI platforms
• Implement best practices for report design, performance optimization, and security
• Contribute to audit, compliance, and data quality initiatives

Standardization and Optimization

• Drive standardization and consolidation of BI tools and reporting frameworks
• Monitor usage patterns, identify inefficiencies, and optimize cost and performance
• Build reusable visualization frameworks and design standards

Required Qualifications

• 4+ years of experience in BI development and platform management
• Strong expertise in Power BI / Tableau / SAP BO
• Experience with Azure and GCP environments
• Strong experience in dashboard development, data visualization, and storytelling
• Hands-on experience in data modeling (DAX, Power Query, or equivalent)
• Experience working with enterprise data warehouses and large datasets
• Strong SQL skills for data extraction and validation
• Understanding of BI governance, performance optimization, and security
• Ability to work with cross-functional teams and translate business needs into analytics solutions

Preferred Qualifications

• Experience with Power BI tenant administration and capacity management
• Familiarity with CI/CD pipelines for BI deployments
• Exposure to enterprise monitoring and support environments
• Experience in BI migration or transformation projects
• Understanding of modern data architectures (data lake, lakehouse, cloud analytics platforms)

About CNH

Connect and Heal (CNH) is a healthcare organization focused on transforming healthcare delivery through technology-enabled solutions, clinical excellence, and exceptional patient experiences. We build scalable digital platforms that support healthcare operations, patient engagement, telehealth, and enterprise healthcare services.

Role Summary

We are seeking a highly motivated Engineering Lead to drive the design, development, and delivery of scalable technology solutions that support CNH's business growth and healthcare operations. The role requires a strong blend of technical expertise, people leadership, architecture oversight, and execution excellence.

The Engineering Lead will lead engineering teams, collaborate with Product, Operations, Clinical, and Business stakeholders, and ensure delivery of high-quality, secure, and scalable products.

Key Responsibilities

Technical Leadership

• Lead the design, development, and deployment of scalable applications and platforms.
• Drive engineering best practices, coding standards, architecture reviews, and technical governance.
• Ensure system reliability, performance, security, and scalability.
• Evaluate and implement emerging technologies to improve product capabilities and engineering efficiency.

Team Leadership

• Build, mentor, and manage high-performing engineering teams.
• Conduct performance reviews, coaching, and career development discussions.
• Foster a culture of accountability, innovation, collaboration, and continuous learning.
• Support hiring and talent development initiatives.

Product & Delivery Management

• Partner with Product Managers and business stakeholders to translate business requirements into technical solutions.
• Drive sprint planning, prioritization, estimation, and delivery management.
• Ensure timely and high-quality execution of engineering roadmaps.
• Manage risks, dependencies, and technical debt effectively.

Stakeholder Management

• Collaborate with Operations, Clinical, Customer Success, and Business teams.
• Communicate project progress, risks, and outcomes to leadership.
• Support strategic initiatives through technology-driven solutions.

Quality & Compliance

• Ensure adherence to information security, data privacy, and healthcare compliance requirements.
• Establish monitoring, testing, and release management processes.
• Drive automation, observability, and operational excellence.

Qualifications

• Bachelor's or Master's degree in Engineering, Computer Science, or related field.
• 8–12+ years of software engineering experience.
• 3–5+ years of experience leading engineering teams.
• Experience building and scaling enterprise-grade applications.

Technical Skills & Expertise

• Strong proficiency in modern programming languages such as Java, Python, Node.js, Golang, or .NET.
• Hands-on experience in designing and managing RESTful APIs, API Gateways, and Microservices Architecture.
• Strong knowledge of CI/CD Automation using tools such as Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps, or similar platforms.
• Experience in DevOps practices, including Infrastructure as Code (IaC), containerization (Docker), orchestration (Kubernetes), and cloud-native deployments.
• Expertise in cloud platforms such as AWS, Azure, or GCP.
• Experience implementing monitoring, logging, and observability solutions.
• Familiarity with modern databases, distributed systems, and high-availability architectures.
• Exposure to AI/ML tools, Generative AI solutions, LLMs, AI-assisted development tools (GitHub Copilot, Cursor, ChatGPT, etc.), and their integration into enterprise applications.
• Understanding of healthcare interoperability standards, APIs, and data security principles is desirable.

Additional Responsibilities

• Drive adoption of AI-powered engineering practices to improve developer productivity, code quality, and operational efficiency.
• Establish and maintain robust CI/CD pipelines to enable faster and more reliable software releases.
• Lead DevOps transformation initiatives, promoting automation, infrastructure scalability, and engineering excellence.
• Define and govern enterprise-wide API strategy, standards, security, and lifecycle management.
• Evaluate emerging technologies and AI innovations to support CNH's digital healthcare roadmap.

Preferred Candidate Profile

• 10–15 years of experience in software engineering, with 4–6 years in engineering leadership roles.
• Proven experience leading teams building cloud-native, API-first, AI-enabled platforms.
• Strong background in DevOps, CI/CD automation, platform engineering, and digital transformation initiatives.
• Experience managing engineering teams delivering mission-critical products at scale.

CNH offers an opportunity to build impactful healthcare technology solutions that improve access, quality, and patient outcomes while working with a passionate and mission-driven team.

Position: Team Lead – Data Engineering

We are looking for an experienced Team Lead / Architect – Data Engineer to design, architect, and lead scalable cloud-based data platforms.

Key Responsibilities:

• Design and architect scalable, high-performance data solutions.
• Lead and mentor a team of data engineers.
• Build and optimize large-scale data pipelines.
• Drive architectural decisions and technical strategy.
• Ensure data quality, governance, and security best practices.
• Collaborate with cross-functional teams for end-to-end delivery.

Required Skills:

• Strong hands-on experience in Java & Python.
• Strong expertise in SQL and Big Data technologies.
• Hands-on experience with Google Cloud Platform (GCP).
• Experience with Apache Airflow for workflow orchestration.
• Strong understanding of distributed systems and data architecture.
• Experience in CI/CD pipelines (mandatory).
• Experience in data warehousing and ETL processes.
• Excellent leadership and stakeholder management skills.

Good to Have:

• Experience with Dataflow (Apache Beam).
• Experience designing enterprise-level data platforms.
• Exposure to DevOps best practices.

Job Summary

We are seeking an experienced BI Developer with strong expertise in Power BI/Tableau and Azure to support large-scale business intelligence initiatives, including report development, dashboarding, and platform transformation.

The ideal candidate will have a strong focus on data visualization, storytelling, and analytics delivery, along with experience in BI platform management and migration. You will play a key role in designing intuitive, high-impact dashboards and ensuring business users have actionable insights readily available.

Key Responsibilities

BI Development, Visualization and Dashboarding

• Design and implement reports, interactive dashboards, and data models using BI tools to enable data-driven decision-making
• Work with Data Product Owners and stakeholders to understand analytical goals and translate them into impactful dashboards
• Develop intuitive, visually compelling dashboards with a strong focus on usability and storytelling
• Identify and rapidly resolve issues related to data visualization, performance, and user experience
• Ensure consistency, standardization, and reusability across dashboards and reporting layers

BI Migration and Transformation

• Lead or support migration of reports and dashboards across BI platforms (e.g., Tableau to Power BI)
• Translate existing reports into optimized, scalable Power BI solutions
• Improve reporting frameworks during migration for better performance and usability

Data Modeling and Integration

• Develop robust data models using Power BI (DAX, Power Query) or equivalent tools
• 
  
• Work closely with data engineers, analysts, and scientists to build reliable datasets for reporting
• Validate and optimize data pipelines feeding BI systems
• Ensure data accuracy, consistency, and governance across reporting solutions

Collaboration and Cross-Functional Delivery

• Collaborate closely with data engineers, data analysts, and data scientists to deliver end-to-end analytics solutions
• Work with business stakeholders to refine requirements and improve reporting outcomes
• Contribute to building scalable and reusable reporting frameworks

BI Platform Administration and Management

• Administer BI platforms such as Power BI, Tableau, or SAP BO
• Manage workspaces, access control, tenant settings, and user permissions
• Handle capacity planning, cost optimization, and resource utilization
• Perform regular housekeeping and monitor usage to optimize platform efficiency

Platform Maintenance and Reliability

• Ensure platform performance, scalability, security, compliance, and uptime
• Plan and execute platform maintenance, including patching and release management
• Support platform “evergreening” and manage audit logs for troubleshooting

Infrastructure, Deployment and Monitoring

• Support installation, configuration, and setup of BI tools and environments
• Design and implement deployment architecture for BI solutions
• Build automated health checks, monitoring, and alerting mechanisms
• Integrate monitoring with enterprise systems (e.g., NOC) and ensure support readiness

Governance and Quality

• Ensure data and reporting governance across dashboards and BI platforms
• Implement best practices for report design, performance optimization, and security
• Contribute to audit, compliance, and data quality initiatives

Standardization and Optimization

• Drive standardization and consolidation of BI tools and reporting frameworks
• Monitor usage patterns, identify inefficiencies, and optimize cost and performance
• Build reusable visualization frameworks and design standards

Required Qualifications

• 4+ years of experience in BI development and platform management
• Strong expertise in Power BI / Tableau / SAP BO
• Experience with Azure and GCP environments
• Strong experience in dashboard development, data visualization, and storytelling
• Hands-on experience in data modeling (DAX, Power Query, or equivalent)
• Experience working with enterprise data warehouses and large datasets
• Strong SQL skills for data extraction and validation
• Understanding of BI governance, performance optimization, and security
• Ability to work with cross-functional teams and translate business needs into analytics solutions

Preferred Qualifications

• Experience with Power BI tenant administration and capacity management
• Familiarity with CI/CD pipelines for BI deployments
• Exposure to enterprise monitoring and support environments
• Experience in BI migration or transformation projects
• Understanding of modern data architectures (data lake, lakehouse, cloud analytics platforms)

Location: Bangalore (Hybrid/Onsite)

Experience: 5–8 Years

Work location -Manyata Tech park

Job Description

We are seeking a skilled GCP Data Engineer with 5–8 years of experience in designing, developing, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate should have strong expertise in Google Cloud Platform (GCP), Python, PySpark, SQL, and Data Engineering concepts.

Key Responsibilities

• Design, build, and optimize scalable ETL/ELT data pipelines.
• Develop and maintain data processing solutions using Python and PySpark.
• Work with large-scale structured and unstructured datasets.
• Implement data ingestion, transformation, and data quality frameworks.
• Build and manage data solutions on Google Cloud Platform (GCP).
• Develop and optimize complex SQL queries, stored procedures, and data models.
• Collaborate with business stakeholders, data analysts, and cross-functional teams to understand data requirements.
• Monitor, troubleshoot, and improve data pipeline performance and reliability.
• Ensure data governance, security, and compliance standards are followed.
• Support data warehousing and analytics initiatives.

Required Skills

• 5–8 years of experience in Data Engineering.
• Strong programming experience in Python.
• Hands-on experience with PySpark and distributed data processing.
• Strong expertise in SQL and database performance tuning.
• Experience with Google Cloud Platform (GCP) services such as:
• BigQuery
• Cloud Storage
• Dataflow
• Dataproc
• Cloud Composer
• Pub/Sub
• Experience in designing ETL/ELT workflows.
• Knowledge of data warehousing concepts and dimensional modeling.
• Experience with version control tools such as Git.
• Strong problem-solving and analytical skills.

Preferred Skills

• Experience with CI/CD pipelines and DevOps practices.
• Exposure to orchestration tools like Airflow/Cloud Composer.
• Experience working in Agile/Scrum environments.
• Knowledge of streaming data processing and real-time data pipelines.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Job Title:  RPA Developer

Experience: 4+ Years

Location: Hybrid (Bangalore)

Job Summary

We're looking for an RPA Developer with hands-on experience in Microsoft Power Automate and Automation Anywhere. The ideal candidate will bring a mix of RPA development and platform administration experience (minimum 6 months in admin activities) and a passion for building scalable automation solutions.

Key Responsibilities

• Design, develop, and deploy automation solutions using Microsoft Power Automate and Automation Anywhere.
• Identify and automate business processes to improve efficiency.
• Integrate automations with enterprise applications and cloud services.
• Administer and maintain Power Automate and Automation Anywhere environments.
• Monitor platform performance, security, governance, and compliance.
• Troubleshoot and enhance existing automation workflows.

Required Skills

• Strong hands-on experience with Microsoft Power Automate and Automation Anywhere.
• Experience in both RPA development and platform administration (minimum 6 months of administration experience).
• Proficiency in Python, JavaScript, VBScript, or .NET.
• Experience with at least one major cloud platform: Azure, AWS, or GCP.
• Experience integrating automation solutions with enterprise systems and APIs.
• Strong problem-solving and stakeholder communication skills.

Preferred Skills

• Certifications in Microsoft Power Platform/Power Automate or Automation Anywhere.
• Experience with AI Builder, Process Advisor, Dataverse, and Jira.
• Exposure to Pega or other BPM platforms.

Position: Team Lead – Data Engineering

Client: NucleusTeq

We are looking for an experienced Team Lead / Architect – Data Engineer to design, architect, and lead scalable cloud-based data platforms.

Key Responsibilities:

·     Design and architect scalable, high-performance data solutions.

·     Lead and mentor a team of data engineers.

·     Build and optimize large-scale data pipelines.

·     Drive architectural decisions and technical strategy.

·     Ensure data quality, governance, and security best practices.

·     Collaborate with cross-functional teams for end-to-end delivery.

Required Skills:

·     Strong hands-on experience in Java & Python.

·     Strong expertise in SQL and Big Data technologies.

·     Hands-on experience with Google Cloud Platform (GCP).

·     Experience with Apache Airflow for workflow orchestration.

·     Strong understanding of distributed systems and data architecture.

·     Experience in CI/CD pipelines (mandatory).

·     Experience in data warehousing and ETL processes.

·     Excellent leadership and stakeholder management skills.

Good to Have:

·     Experience with Dataflow (Apache Beam).

·     Experience designing enterprise-level data platforms.

·     Exposure to DevOps best practices.

Hiring: GCP Data Engineer (FTE)

📍 Location: Bangalore | Chennai | Pune | Gurgaon | Kolkata

💼 Employment Type: Full-Time

Notice Period - Immediate Joiner ( Serving Notice Period )

Work Mode - Hybrid

We are looking for experienced GCP Data Engineers with strong expertise in building scalable cloud data solutions.

Required Skills:

✔ GCP Data Engineering Experience

✔ BigQuery

✔ SQL & Python

✔ PySpark / Apache Spark

✔ Apache Beam / Dataflow

✔ ETL / ELT Pipeline Development

✔ Airflow / Cloud Composer

Responsibilities:

• Design and develop scalable ETL/ELT pipelines on GCP
• Build and optimize BigQuery solutions
• Process large-scale structured/unstructured data using Spark
• Develop automated workflows and cloud-native data pipelines
• Work with GCP services like Dataflow, Dataproc, Cloud Storage, etc.
• 
  

Good to Have:

• Google Cloud Certifications (Professional Data Engineer / Solution Architect)
• Experience with BigTable, Cloud SQL, Spanner, NoSQL databases

🎓 Qualification: Bachelor’s / Master’s in CS, Engineering, or related field

Key Responsibilities 

• Design, develop, and maintain scalable web applications using Node.js, React.js, and Next.js 
• Build robust RESTful APIs and backend services 
• Develop responsive and high-performance user interfaces 
• Work with cloud services on AWS and/or GCP for deployment and infrastructure 
• Collaborate with cross-functional teams including product, design, and QA 
• Optimize applications for maximum speed and scalability 
• Ensure code quality through best practices, code reviews, and testing 
• Troubleshoot and debug applications 

Required Skills 

• Strong experience in Node.js (backend development) 
• Proficiency in React.js and Next.js with product development experience
• Experience in building REST APIs and microservices architecture 
• Hands-on experience with cloud platforms: 
• Amazon Web Services (AWS) 
• Google Cloud Platform (GCP) 
• Strong knowledge of JavaScript (ES6+), HTML5, and CSS3 
• Experience with databases (SQL/NoSQL such as MongoDB, PostgreSQL) 
• Familiarity with version control tools like Git 
• Understanding of CI/CD pipelines and DevOps practices  

Role: Data Engineer

 Experience: 5+ Yrs

Type: Hybrid (3 Days a week)

Location: Chennai, Bangalore, Hyderabad, Pune, Kolkatta

End Client: Cognizant

Contract Duration: 6 Months

Shift:- 10 AM - 7 PM IST

Must Have: 

* Strong experience in Python

* Expertise in Data Engineering Frameworks

* Hands-on experience with ETL processes

* CI/CD

* Experience working on GCP (Google Cloud Platform)

About My Client Company

We're building the learning infrastructure that transforms AI agents into true digital workers. While today's agents can reason and plan, they fail to do meaningful work because they lack real experience operating in apps. My Client Product gives agents continuously improving, reusable skills across 1000+ production-grade app connectors including Gmail, Linear, and Hubspot. We handle authentication, tool routing, retries, failure handling, and observability, making every action safe and dependable.

About the Role

Every enterprise is racing to make AI work — not as a demo, but as infrastructure that runs their business. My Client Product is becoming the critical layer that makes this possible: the platform that connects AI agents to 250+ real-world applications with production-grade auth, execution, and reliability.

We've built this for the cloud. Now we need to build it for the enterprise — and that means rethinking the platform from the ground up with the right abstractions, primitives, and architectural decisions that let us serve a massive, diverse set of enterprise customers without bespoke engineering for each one. This is a founding role.

Your Impact

• Agent infrastructure platform: The foundational layer that enterprise AI agents run on — governance, observability, and control planes for MCP-powered agent ecosystems. You'll define how organizations monitor, audit, and manage AI agents operating at scale across their systems
• The integration gateway: The secure, reliable bridge between an enterprise's AI agents and the outside world — every SaaS tool, internal system, and API they need to act on. Not just connectors, but a platform-grade gateway with the right trust, permissioning, and routing primitives
• Platform primitives for scale: Multi-tenancy, isolation, configuration, and extensibility abstractions that let Composio serve thousands of enterprise customers without linear engineering cost
• Enterprise-grade architecture: Deployment flexibility, security, and compliance as first-class platform capabilities — not bolted-on afterthoughts
• The repeatable deployment motion: Turn enterprise onboarding from a services engagement into a product experience. Shorter cycles, fewer custom touches, more self-serve

What you bring

• You've built platforms at genuine scale — not just high user counts, but high complexity: many customer types, deployment models, and integration surfaces
• You think in abstractions and primitives. Your instinct is to find the right foundational model, not to solve each problem individually
• You've shipped enterprise product capabilities (deployment flexibility, security, admin tooling, compliance) and understand them as product problems, not just checkboxes
• You've built or shipped an AI product — or you're the person who can't stop tinkering. You're building agents on weekends, stress-testing the latest models, experimenting with MCP, and forming your own opinions on where agent architectures are headed. You have a point of view on this space, not just a resume line
• You're a force multiplier. When you join a team, the entire product moves faster because the platform decisions are right

Skills & Expertise

Platform Engineering, AI Infrastructure, Agentic AI, AI Agents, MCP (Model Context Protocol), Distributed Systems, Enterprise Architecture, Multi-Tenant Architecture, Backend Platform Engineering, Enterprise SaaS, API Platform Engineering, Integration Platforms, SaaS Connectors, Cloud Infrastructure, AWS, GCP, Kubernetes, Docker, Terraform, Microservices, Event-Driven Architecture, API Gateway, OAuth 2.0, RBAC, IAM, Observability, OpenTelemetry, Prometheus, Grafana, Reliability Engineering, SRE, Python, Golang, Node.js, TypeScript, REST APIs, GraphQL, AI Orchestration, LLM Infrastructure, LangChain, LangGraph, OpenAI APIs, Claude APIs, RAG, Workflow Automation, AI Tool Routing, Enterprise Security, Compliance Engineering, Deployment Architecture, Configuration Management, Extensible Systems, Scalability Engineering, High-Scale Systems, Technical Strategy, Platform Primitives, Developer Platforms, Enterprise Integrations, Infrastructure Engineering, Founding Engineer Mindset.

This role demands deep platform thinking. You've designed systems where the abstractions were the product — where getting the primitives right meant the difference between a product that scales and one that drowns in customer-specific code.

You've done this within large organizations and seen what "enterprise-grade" actually means when thousands of teams depend on your platform. But you've also operated in environments where you had to build fast, make tradeoffs, and ship before the architecture was perfect.

The combination matters. Big-company pattern recognition with small-company intensity.

What We Offer

• Lunch and dinner are provided in the office
• $200/month learning and development budget
• $1,000/month AI tool experimentation budget to automate, accelerate, and improve how you work
• High-ownership role with direct exposure to leadership and company-building decisions
• Competitive salary and equity

GCP Data Engineer

Experience: 8 – 15 yrs

Grade: C2/D1

Skill: GCP + Python/Pyspark

NP: Immediate joiners

• 8+ years of hands-on experience in Python.
• 8+ years of hands-on experience in Data Engineering.
• 5+ Years of hands-on experience in GCP Big Query.
• Experience in building scalable data pipelines and automation frameworks.
• Experience migrating data and pipelines from SQL Server to GCP Big Query.
• Familiarity with CI/CD tools and Agile methodologies.
• Good understanding on Data Governance, Data Quality, Metadata, Lineage
• Expertise in Data Model design in Big query.
• Expertise in writing optimal Big query SQL and Stored Proc.
• Expertise in GCS Cloud Storage, Pub Sub, Cloud Composer, DAG, Apache Airflow, Data Flow, Data Proc, Data Plex, Cloud Run.
• Expertise in Vertex AI and Feature Store.
• Expertise in Spark and Apache Beam is desirable.

Email resumes to: naveenkb @ 10xscale.ai

GCP DevOps Engineer – Job Description (2+ Years Experience)

We are looking for a motivated and skilled GCP DevOps Engineer with 2+ years of hands-on experience in cloud infrastructure, CI/CD pipelines, automation, and deployment processes on Google Cloud Platform (GCP). The ideal candidate should have experience in cloud operations, monitoring, containerization, and DevOps best practices.

Key Responsibilities

• Design, implement, and maintain CI/CD pipelines for application deployment.
• Manage and monitor cloud infrastructure on Google Cloud Platform (GCP).
• Work with development and QA teams to automate build, deployment, and release processes.
• Handle infrastructure provisioning using Infrastructure as Code (IaC) tools like Terraform.
• Manage containerized applications using Docker and Kubernetes (GKE).
• Monitor system performance, troubleshoot issues, and ensure high availability.
• Implement security best practices, backup strategies, and access management.
• Support production deployments and resolve environment-related issues.
• Maintain documentation for infrastructure, deployment, and operational procedures.

Required Skills

• 2+ years of experience in DevOps or Cloud Engineering.
• Hands-on experience with Google Cloud Platform (GCP).
• Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Cloud Build.
• Knowledge of Docker and Kubernetes (GKE).
• Experience with Terraform or other IaC tools.
• Strong understanding of Linux administration and shell scripting.
• Experience with version control tools like Git.
• Knowledge of monitoring tools such as Prometheus, Grafana, or Cloud Monitoring.
• Understanding of networking, security, and cloud architecture concepts.

Good to Have

• Experience with Ansible or other configuration management tools.
• Knowledge of Python, Bash, or scripting languages.
• GCP Certifications are an added advantage.
• Exposure to Agile/Scrum environments.

Mandatory Skills: ETL, Data Warehousing, Python, GCP Services

Required Skills:

● Bachelor’s degree in Computer Science or similar field or equivalent work experience.

● 4+ years of experience on Data Warehousing, Data Engineering or Data Integration projects.

● Expert with data warehousing concepts, strategies, and tools.

● Strong SQL background.

● Strong knowledge of relational databases like SQL Server, PostgreSQL, MySQL.

● Strong experience in GCP & Google BigQuery, Cloud SQL, Composer (Airflow), Dataflow, Dataproc, Cloud Function and GCS

● Good to have knowledge on SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS).

● Knowledge of AWS and Azure Cloud is a plus.

● Experience in Informatica Power exchange for Mainframe, Salesforce, and other new-age data sources.

● Experience in integration using APIs, XML, JSONs etc.

● In-depth understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework, data-warehousing and Data Lakes

● Good understanding of SDLC, Agile and Scrum processes.

● Strong problem-solving, multi-tasking, and organizational skills.

● Highly proficient in working with large volumes of business data and strong understanding of database design and implementation.

● Good written and verbal communication skills.

● Demonstrated experience of leading a team spread across multiple locations.

Role & Responsibilities:

● Work with business users and other stakeholders to understand business processes.

● Ability to design and implement Dimensional and Fact tables

● Identify and implement data transformation/cleansing requirements

● Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform and load data from various systems to the Enterprise Data Warehouse

● Develop conceptual, logical, and physical data models with associated metadata including data lineage and technical data definitions

● Design, develop and maintain ETL workflows and mappings using the appropriate data load technique

● Provide research, high-level design, and estimates for data transformation and data integration from source applications to end-user BI solutions.

● Provide production support of ETL processes to ensure timely completion and availability of data in the data warehouse for reporting use.

● Analyze and resolve problems and provide technical assistance as necessary. Partner with the BI team to evaluate, design, develop BI reports and dashboards according to functional specifications while maintaining data integrity and data quality.

● Work collaboratively with key stakeholders to translate business information needs into well-defined data requirements to implement the BI solutions.

● Leverage transactional information, data from ERP, CRM, HRIS applications to model, extract and transform into reporting & analytics.

● Define and document the use of BI through user experience/use cases, prototypes, test, and deploy BI solutions.

● Develop and support data governance processes, analyze data to identify and articulate trends, patterns, outliers, quality issues, and continuously validate reports, dashboards and suggest improvements.

● Train business end-users, IT analysts, and developers.

Immediate Hiring: GCP DevOps Engineer | Mumbai & Bengaluru (On-site)

OpsTree Global is urgently hiring a GCP DevOps Engineer with 4–9 years of experience for immediate requirements in Mumbai and Bengaluru.

Key Skills

• Google Cloud Platform (GCP)
• Terraform / Infrastructure as Code (IaC)
• Kubernetes & Helm Charts
• CI/CD – Jenkins, GitLab CI, GitHub Actions
• Linux Administration
• Scripting – Python / Go / Java
• 
  

Role Responsibilities

• Build and manage scalable cloud infrastructure on GCP
• Automate deployments and infrastructure provisioning
• Ensure system reliability, monitoring, and performance optimization
• Collaborate with development and operations teams for seamless delivery

📍 Locations: Mumbai & Bengaluru (On-site)

⚡ Immediate Joiners Preferred

💼 Experience: 4–9 Years

Job Title: AI/ML Architect Experience: 10+ years Industry: Media Preferred

Role Summary:

The AI/ML Architect shapes the AI strategy and leads enterprise-level architecture for multimodal AI in the media organization. This includes building capabilities across media understanding, LLM workflows, multimodal RAG, real-time metadata enrichment, content intelligence, personalization, and scalable AI platform infrastructure.

Detailed Responsibilities Enterprise Architecture & Strategy

·       Define long-term AI architecture roadmap across:

o  NLP, CV, ASR, video AI

o  Multimodal LLMs

o  Recommendation systems

o  Content moderation & compliance

o  RAG & knowledge systems

o  Agentic automation

·       Architect scalable ingestion pipelines for high-volume media (10K+ hours of video).

·       Define standards for model lifecycle, governance, auditability, and lineage.

Platform & Infrastructure

·       Architect GPU clusters, distributed compute, and cloud AI platforms.

·       Oversee integrations of:

o  Media Asset Management (MAM)

o  Content Management Systems (CMS)

o  Data lake/lakehouse

o  Vector databases

o  Observability platforms

Governance & Compliance

·       Ensure compliance with:

o  Content safety guidelines

o  Copyright/IP protection

o  Data privacy laws

o  Responsible AI standards (NIST AI RMF)

Innovation & Leadership

·       Evaluate emerging multimodal and generative AI technologies.

·       Drive adoption of LLMOps practices and agentic AI frameworks.

·       Present architecture strategies to C-level stakeholders.

Must-Have Skills

·       Deep expertise in multimodal AI (text–image–audio–video).

·       Mastery of LLMs and their ecosystem (fine-tuning, adapters, vector search).

·       Expert-level cloud architecture (Azure/AWS/GCP).

·       Strong experience in enterprise-scale MLOps + LLMOps.

·       Deep exposure to media processing at scale.

Preferred Skills

·       Knowledge of video generation, audio synthesis, and generative media workflows.

·       Experience in building AI COEs or platform teams.

Qualifications

·       10+ years in AI/ML with at least 3+ years architecting enterprise systems.

·       Master’s/Ph.D. (preferred).

Designation: Cloud Sales Specialist (AWS/GCP/AZURE) (Field Sales)

Location: Mumbai (Andheri West) / Bengaluru

Experience: 5 to 10 Years relevant experience

Industry: Cloud Solutions/IT Services

About the Role

We are looking for a high-performing Sales Specialist (Field Sales) with strong industry connect & solution selling and a proven ability to close high-value deals.

This role is ideal for someone who is a true sales hunter, with strong CXO-level connect, ability to independently drive revenue through field engagement, principal vendors’ connections and strategic selling.

Important Note 

This role strictly requires hands-on Cloud Sales experience and existing CXO connections. Profiles from non-cloud or purely generic IT sales backgrounds will not be considered.

Key Responsibilities

• Own and drive end-to-end field sales for Cloud Services (AWS/Azure/GCP)
• Manage the region by Identifying, acquiring, and growing new business opportunities
• Build and leverage CXO-level relationships to drive business
• in-person client meetings, presentations, and solution positioning
• Collaborate with pre-sales & technical teams for solution-based selling
• Manage complete sales cycle: prospecting → negotiation → closure
• Consistently achieve and exceed sales targets
• Maintain strong pipeline management and forecasting discipline

Must-Have Experience

• 5-10 years in core Cloud Sales (AWS / Azure / GCP / Cloud Solutions)
• Proven track record in closing high-value deals
• Strong existing CXO / decision-maker connects (mandatory)
• Hands-on experience in field sales & direct client engagement
• Strong understanding of cloud ecosystem & solution selling

What Makes You a Great Fit

• A go-getter sales professional with strong hunting ability
• Ability to open doors, build trust, and close deals independently
• Strong network across decision-makers and business stakeholders
• High ownership mindset with a target-driven approach

What’s in It for You

• Opportunity to work directly with CXOs and key decision-makers
• Fast-track growth into leadership roles
• Exposure to leading cloud ecosystems (AWS / Azure / GCP)

Your Mission: The Role

solving for better.

You are a reliability-owning, hands-on solver. Not just a "break-fix engineer."

As a DRI (directly responsible individual) for our clients' most critical systems, you’ll be the go-to expert within the squad that ensures their environments are secure, reliable, and optimized 24/7. You will deliver measurable impact – improved uptime, faster response times, and real cost savings. Not just closed tickets. Not just alerts. Real outcomes you engineer yourself.

You will lead the charge on technical execution, from complex troubleshooting and root cause analysis to engineering proactive, automated solutions. This role is about building the future of reliable cloud operations and shipping it into today's production environments.

Your Responsibilities

what you will wake up to solve.

This isn’t a “manage tickets” role. You are the architect, the executioner and the DRI for our Cloud Managed Services GTM, deploying solutions that turn operational noise into hardened outcomes. Here’s how you’ll make your mark:

• Own Service Reliability: You will be the go-to technical expert for 24/7 cloud operations and incident management. You'll ensure strict adherence to SLOs by getting your hands dirty, leading high-stakes troubleshooting to deliver a superior client experience.
• Engineer the Blueprint: You'll translate client needs into scalable, automated, and secure cloud architectures. You will write and maintain the operational playbooks and Infrastructure as Code (IaC) that your squad uses every day.
• Automate with Intelligence: You'll lead the charge from the keyboard to futurify our operations. You'll embed AI-driven automation, predictive monitoring, and AIOps into core processes to eliminate toil and preempt incidents.
• Drive FinOps & Impact: You'll own the technical execution of the FinOps framework. You will continuously analyze, configure, and optimize cloud spend for clients through hands-on engineering.
• Be the Expert in the Room: You'll share your knowledge through internal demos, documentation, and technical deep dives, representing the deep expertise that turns operational complexity into business resilience.
• Mentor & Elevate: You will be a technical mentor for your peers. Through code reviews and collaborative problem-solving, you'll help build a high-performing squad that lives the “Always Hardened” mindset.

Experience & Relevance

We are looking for future technology leaders, not just coders. We value raw intelligence, analytical rigor, and an obsessive passion for technology over any prior experience.

• Cloud Operations Pedigree: 3+ years of experience in GCP cloud infrastructure, with a significant portion in a cloud managed services.
• Commercial Acumen: Proven track record of building and scaling a net-new managed services business.
• Client-Facing Tech Acumen: 2+ years of experience in a client-facing technical role, acting as the trusted advisor for cloud operations, security, and reliability.

Functional Skills:

• Service Delivery Mindset: A deep understanding of MSP business models, SLAs, and the importance of client satisfaction in an operational context.
• Client Engagement: Ability to ask appropriate questions to get to the heart of an operational issue and win trust with stakeholders.
• Cross-Functional Catalyst: Thrive in multi-disciplinary teams, bringing together operations, security, and development teams.
• Repository builder: Creates reusable frameworks, IaC modules, and operational playbooks for scale.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Your Mission: The Role

solving for better.

You are a reliability-owning, hands-on solver. Not just a "break-fix engineer."

As a DRI (directly responsible individual) for our clients' most critical systems, you’ll be the go-to expert within the squad that ensures their environments are secure, reliable, and optimized 24/7. You will deliver measurable impact – improved uptime, faster response times, and real cost savings. Not just closed tickets. Not just alerts. Real outcomes you engineer yourself.

You will lead the charge on technical execution, from complex troubleshooting and root cause analysis to engineering proactive, automated solutions. This role is about building the future of reliable cloud operations and shipping it into today's production environments.

Your Responsibilities

what you will wake up to solve.

This isn’t a “manage tickets” role. You are the architect, the executioner and the DRI for our Cloud Managed Services GTM, deploying solutions that turn operational noise into hardened outcomes. Here’s how you’ll make your mark:

• Own Service Reliability: You will be the go-to technical expert for 24/7 cloud operations and incident management. You'll ensure strict adherence to SLOs by getting your hands dirty, leading high-stakes troubleshooting to deliver a superior client experience.
• Engineer the Blueprint: You'll translate client needs into scalable, automated, and secure cloud architectures. You will write and maintain the operational playbooks and Infrastructure as Code (IaC) that your squad uses every day.
• Automate with Intelligence: You'll lead the charge from the keyboard to futurify our operations. You'll embed AI-driven automation, predictive monitoring, and AIOps into core processes to eliminate toil and preempt incidents.
• Drive FinOps & Impact: You'll own the technical execution of the FinOps framework. You will continuously analyze, configure, and optimize cloud spend for clients through hands-on engineering.
• Be the Expert in the Room: You'll share your knowledge through internal demos, documentation, and technical deep dives, representing the deep expertise that turns operational complexity into business resilience.
• Mentor & Elevate: You will be a technical mentor for your peers. Through code reviews and collaborative problem-solving, you'll help build a high-performing squad that lives the “Always Hardened” mindset.

Experience & Relevance

We are looking for future technology leaders, not just coders. We value raw intelligence, analytical rigor, and an obsessive passion for technology over any prior experience.

• Cloud Operations Pedigree: 3+ years of experience in GCP cloud infrastructure, with a significant portion in a cloud managed services.
• Commercial Acumen: Proven track record of building and scaling a net-new managed services business.
• Client-Facing Tech Acumen: 2+ years of experience in a client-facing technical role, acting as the trusted advisor for cloud operations, security, and reliability.

Functional Skills:

• Service Delivery Mindset: A deep understanding of MSP business models, SLAs, and the importance of client satisfaction in an operational context.
• Client Engagement: Ability to ask appropriate questions to get to the heart of an operational issue and win trust with stakeholders.
• Cross-Functional Catalyst: Thrive in multi-disciplinary teams, bringing together operations, security, and development teams.
• Repository builder: Creates reusable frameworks, IaC modules, and operational playbooks for scale.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

We are seeking a skilled Data Engineer to join the AI Platform Capabilities team supporting the UDP Uplift program.

In this role, you will design, build, and test standardized data and AI platform capabilities across a multi-cloud environment (Azure & GCP).

You will collaborate closely with AI use case teams to develop:

• Scalable data pipelines
• Reusable data products
• Foundational data infrastructure

Your work will support advanced AI solutions such as:

• GenAI
• RAG (Retrieval-Augmented Generation)
• Document Intelligence

Key Responsibilities

• Design and develop scalable ETL/ELT pipelines for AI workloads
• Build and optimize data pipelines for structured & unstructured data
• Enable context processing & vector store integrations
• Support streaming data workflows and batch processing
• Ensure adherence to enterprise data models, governance, and security standards
• Collaborate with DataOps, MLOps, Security, and business teams (LBUs)
• Contribute to data lifecycle management for AI platforms

Required Skills

• 5–7 years of hands-on experience in Data Engineering
• Strong expertise in Python and advanced SQL
• Experience with GCP and/or Azure cloud-native data services
• Hands-on experience with PySpark / Spark SQL
• Experience building data pipelines for ML/AI workloads
• Understanding of CI/CD, Git, and Agile methodologies
• Knowledge of data quality, governance, and security practices
• Strong collaboration and stakeholder management skills

Nice-to-Have Skills

• Experience with Vector Databases / Vector Stores (for RAG pipelines)
• Familiarity with MLOps / GenAIOps concepts (feature stores, model registries, prompt management)
• Exposure to Knowledge Graphs / Context Stores / Document Intelligence workflows
• Experience with DBT (Data Build Tool)
• Knowledge of Infrastructure-as-Code (Terraform)
• Experience in multi-cloud deployments (Azure + GCP)
• Familiarity with event-driven systems (Kafka, Pub/Sub) & API integrations

Ideal Candidate Profile

• Strong data engineering foundation with AI/ML exposure
• Experience working in multi-cloud environments
• Ability to build production-grade, scalable data systems
• Comfortable working in cross-functional, fast-paced environments

Location: Bangalore

Experience: 2–5 years

Type: Full-time | On-site

Start: Immediate

Why this role exists

Most systems don’t fail because of one big outage.

They fail because reliability is treated as an afterthought.

Right now, uptime depends too much on individual heroics.

That doesn’t scale.

This role exists to build a reliability system where:

• Uptime is predictable
• Failures are contained
• Escalations don’t depend on leadership

What you’ll do

You will not just monitor systems.

You will own reliability as a product.

1. Drive uptime to production-grade reliability

• Improve system uptime to 99.9% customer-facing SLA within 4 months
• Define and track:
• SLAs / SLOs / error budgets
• Ensure reliability is measured from the customer’s perspective, not internal metrics

2. Build incident response as a system

• Set up a 24/7 incident response rotation across 3 engineers
• Eliminate dependency on leadership (no single escalation point)
• Define:
• Incident severity levels
• Response playbooks
• Escalation protocols
• Ensure fast detection → containment → resolution

3. Contain and fix erratic system behavior

• Identify and resolve:
• Latency spikes
• Downtime incidents
• Integration failures
• Build guardrails to prevent recurrence
• Focus on root cause elimination, not temporary fixes

4. Create continuous reliability feedback loops

• Work closely with engineering teams to:
• Surface recurring failure patterns
• Improve build quality
• Reduce production bugs
• Ensure learnings from incidents directly improve future releases

5. Improve observability and monitoring

• Build dashboards and alerts for:
• System health
• Performance metrics
• Failure signals
• Ensure issues are detected before customers report them

6. Reduce operational fragility

• Remove single points of failure (people, systems, workflows)
• Improve system resilience across:
• Deployments
• Integrations
• Runtime environments

What success looks like

• Uptime reaches 99.9%+ reliably
• Incidents are:
• Detected early
• Contained quickly
• Resolved permanently
• No dependency on a single individual for escalation
• System behavior becomes predictable and stable
• Engineering teams ship with higher reliability confidence

Who you are

• You have 2-5 years of experience in SRE / DevOps / backend systems
• You have worked on production systems with real uptime expectations
• You think in:
• Systems
• Failure modes
• Trade-offs
• You are comfortable debugging live, high-pressure environments

What will make you stand out

• Experience with:
• Distributed systems
• Cloud infrastructure (AWS / Azure / GCP)
• Monitoring & alerting tools
• Have built or improved:
• Incident response systems
• Reliability frameworks
• Strong debugging skills across:
• Infra
• Application
• Integrations

Compensation

₹60,000/month (fixed)

(Aligned with role scope and impact expectations)

Why join

• You will define reliability standards for a production AI platform
• Your work directly impacts:
• Customer trust
• Product performance
• Enterprise readiness
• You will move the system from reactive → predictable

What this role is not

• Not just monitoring dashboards
• Not limited to handling tickets
• Not dependent on escalation to leadership

What this role is

• A builder of reliability systems
• A guardian of uptime and performance
• A multiplier of engineering quality

One question to self-evaluate

Can you build a system where downtime is rare, predictable, and never dependent on a single person?

Job Title : DevOps Engineer

Experience : 3+ Years

Location : Indiranagar, Bengaluru (Work From Office – 5 Days)

Employment Type : Full-Time

Work Timings : 11:00 AM to 7:00 PM IST

Notice Period : Immediate Joiners Preferred

Role Overview :

We are seeking a skilled DevOps Engineer with 3+ years of experience in building and managing scalable cloud-native infrastructure.

The ideal candidate will have strong expertise in Kubernetes and Helm, along with hands-on experience in deploying and maintaining production-grade systems on cloud platforms.

This role offers an opportunity to work in a high-growth startup environment, contributing to both existing systems and new infrastructure development.

Key Responsibilities :

• Design, deploy, and manage scalable infrastructure using Kubernetes.
• Build and maintain CI/CD pipelines for efficient and automated deployments.
• Manage and optimize cloud environments (preferably GCP).
• Implement Infrastructure as Code using Helm/Terraform.
• Monitor system performance and ensure high availability and reliability.
• Handle bug fixes, system improvements, and performance optimization.
• Collaborate with engineering teams to design scalable microservices architecture.
• Implement logging, monitoring, and alerting solutions.
• Ensure security best practices including IAM, secrets management, and network policies.

Mandatory Skills :

• Strong hands-on experience with Kubernetes.
• Expertise in Helm Charts.
• Experience with Google Cloud Platform (GCP).
• Hands-on experience with ArgoCD or similar CI/CD tools.
• Knowledge of CI/CD tools like Jenkins, GitHub Actions, GitLab CI.
• Experience in database hosting and scaling.

Nice to Have :

• Exposure to other cloud platforms (AWS/Azure).
• Experience with modern DevOps and automation tools.
• Ability to quickly learn and adapt to new technologies.

Team & Work Scope :

• No dedicated DevOps team currently – high ownership role.
• Work on both existing systems (maintenance & improvements) and new system builds (greenfield projects).
• Opportunity to shape DevOps practices and infrastructure from scratch.

Preferred Candidate Profile :

• 3+ years of relevant DevOps experience.
• Strong problem-solving and debugging skills.
• Experience working in fast-paced startup environments.
• Understanding of scalability, security, and performance optimization.
• Good communication and collaboration skills.

Hiring Process :

1. Profile Screening
2. GT Assessment
3. Technical Interview – Round 1
4. Technical Interview – Round 2
5. Final Round (if required with US team)

Lead Cloud Reliability Engineer

Job Responsibilities

● Lead and manage the Cloud Reliability teams to provide strong Managed Services support to end-customers.

● Isolate, troubleshoot and resolve issues reported by CMS clients in their cloud environment

● Drive the communication with the customer providing details about the issue, current steps, next plan of action, ETA

● Gather client's requirements related to use of specic cloud services and provide assistance in seing them up and resolving issues

● Create SOPs and knowledge articles for use by the L1 teams to resolve common issues

● Identify recurring issues, perform root cause analysis and propose/implement preventive actions

● Follow change management procedure to identify, record and implement changes

● Plan and deploy OS, security patches in Windows/Linux environment and upgrade k8s clusters

● Identify the recurring manual activities and contribute to automation

● Provide technical guidance and educate team members on development and operations. Monitor metrics and develop ways to improve.

● System troubleshooting and problem-solving across plaorm and application domains. Ability to use a wide variety of open-source technologies and cloud services.

● Build, maintain, and monitor conguration standards.

● Ensuring critical system security through using best-in-class cloud security solutions.

Qualifications

● 4-7 years experience in Cloud Infrastructure and Operations domains and IT operational experience preferably in a global enterprise environment.

● Specialize in one or two cloud deployment platforms: AWS, GCP

● Hands on experience with AWS/GCP services (EKS, ECS, EC2, VPC, RDS, Lambda, GKE, Compute Engine)

● Understanding of one or more programming languages (Python, JavaScript, Ruby, Java, .Net)

● Logging and Monitoring tools (ELK, Stackdriver, CloudWatch)

● Knowledge on Conguration Management tools such as Ansible, Terraform, Puppet, Chef

● Experience working with deployment and orchestration technologies (such as Docker, Kubernetes, Mesos)

● Good analytical, communication, problem solving, and learning skills.

● Knowledge on programming against cloud plaorms such as Google Cloud Platform and lean development methodologies.

● Strong service aitude and a commitment to quality.

● Willingness to work in shifts.

👉 Job Title: Backend Developer

🌟 Experience: 5-7 Years

💡Location: Bangalore

👉 Notice Period :- Immediate Joiners

💡 Work Mode - 5 Days work from Office

( Candidate Serving notice period are preffered)

Role Summary

We are looking for a Backend Engineer to join the Platform Implementation Team, responsible for building scalable, secure, and high-performance backend systems for a multi-cloud Data & AI platform. You will design microservices, develop REST APIs, and enable seamless data integration across enterprise systems like CRM and ERP.

💫 Key Responsibilities

✅ Design and develop scalable microservices and RESTful APIs

✅ Build event-driven architectures for asynchronous processing

✅ Integrate backend systems with cloud platforms (GCP/Azure)

✅ Ensure secure, reliable, and optimized data handling

✅ Collaborate with cross-functional teams (UI, Data, Platform)

✅ Follow best practices in coding, testing, CI/CD, and containerization

💫 Mandatory Skills (Top 3)

✅ Strong backend programming experience (Python / Node.js / Java)

✅ Expertise in API development & Microservices architecture

✅ Hands-on experience with Cloud platforms (GCP or Azure)

Location - Bangalore Skill/Experience Expectations: 1. Total Experience 7-11 yrs 2. 3-4 years in managing scalable production environment 3. 2-4 yr experience in managing Google cloud infrastructure 4. proficient in terraform and any programming language 5. Expert in designing and managing observability solutions 6. 5 yr experience in DevOps and SRE practices and troubleshooting critical incidents.

This role will report to the Chief Technology Officer

You Will Be Responsible For

* Driving decision-making on enterprise architecture and component-level software design to our software platforms' timely build and delivery.

* Leading a team in building a high-performing and scalable SaaS product.

* Conducting code reviews to maintain code quality and follow best practices

* DevOps practice development on promoting automation, including asset creation, enterprise strategy definition, and training teams

* Developing and building microservices leveraging cloud services

* Working on application security aspects

* Driving innovation within the engineering team, translating product roadmaps into clear development priorities, architectures, and timely release plans to drive business growth.

* Creating a culture of innovation that enables the continued growth of individuals and the company

* Working closely with Product and Business teams to build winning solutions

* Led talent management, including hiring, developing, and retaining a world-class team

Ideal Profile

* You possess a Degree in Engineering or a related field and have at least 20+ years of experience as a Software Engineer, with a 10+ years of experience leading teams and at least 4 Years of experience in building a SaaS / Fintech platform.

* Proficiency in MERN / Java / Full Stack.

* Led a team in optimizing the performance and scalability of a product

* You have extensive experience with DevOps environment and CI/CD practices and can train teams.

* You're a hands-on leader, visionary, and problem solver with a passion for excellence.

* You can work in fast-paced environments and communicate asynchronously with geographically distributed teams.

What's on Offer?

* Exciting opportunity to drive the Engineering efforts of a reputed organisation

* Work alongside & learn from best in class talent

* Competitive compensation + ESOPs

Lead Data Engineer

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

What you will wake up to solve.

• Lead Technical Design & Data Architecture: Architect and lead the end-to-end development of scalable, cloud-native data platforms. You’ll guide the squad on critical architectural decisions—choosing between Batch vs. Streaming or ETL vs. ELT—while remaining 100% hands-on, contributing high-quality, production-grade code.
• Build High-Velocity Data Pipelines: Drive the implementation of robust data transports and ingestion frameworks using Python, SQL, and Spark. You will build integration layers that connect heterogeneous sources (SaaS, RDBMS, NoSQL) into unified, high-availability environments like BigQuery, Snowflake, or Redshift.
• Mentor & Elevate the Squad: Foster a culture of technical excellence by mentoring and inspiring a team of data analysts and engineers. Lead deep-dive code reviews, promote best-practice data modeling (Star/Snowflake schema), and ensure the squad adopts modern engineering standards like CI/CD for data.
• Drive AI-Ready Data Strategy: Be the expert in designing data foundations optimized for AI and Machine Learning. You will champion the use of GCP (Dataflow, Pub/Sub, BigQuery) and AWS (Lambda, Glue, EMR) to create "clean room" environments that fuel advanced analytics and generative AI models.
• Partner with Clients as a Technical DRI: Act as the Directly Responsible Individual for client success. Translate ambiguous business questions into elegant data services, manage project deliverables using Agile methodologies, and ensure that the data provided is accurate, consistent, and mission-critical.
• Troubleshoot & Optimize for Scale: Own the reliability of the reporting layer. You will proactively monitor pipelines, troubleshoot complex transformation bottlenecks, and propose ways to improve platform performance and cost-efficiency.
• Innovate and Build Reusable IP: Spearhead the creation of reusable data frameworks, custom operators, and transformation libraries that accelerate future projects and establish Searce’s unique technical advantage in the market.

Welcome to Searce

The AI-Native tech consultancy that's rewriting the rules.

Searce is an AI-native, engineering-led, modern tech consultancy that empowers clients to futurify their business by delivering intelligent, impactful, real business outcomes. Searce solvers co-innovate with clients as their trusted transformational partners ensuring sustained competitive advantage. Searce clients realize smarter, faster, better business outcomes delivered by AI-native Searce solver squads. 

Functional Skills 

the solver personas.

• The Data Architect: This persona deconstructs ambiguous business goals into scalable, elegant data blueprints. They don't just move data; they design the foundation—from schema design to partitioning strategies—that allows data scientists and analysts to thrive, foreseeing technical bottlenecks and making pragmatic trade-offs.
• The Player-Coach: As a hands-on leader, this persona leads from the front by writing exemplary, production-grade SQL and Python while simultaneously mentoring and elevating the skills of the squad. Their success is measured by the team's ability to deliver high-quality, maintainable code and their growth as engineers.
• The Pragmatic Innovator: This individual balances a passion for modern data tech (like Generative AI and Real-time Streaming) with a sharp focus on business outcomes. They champion new tools where they add real value but are disciplined enough to choose stable, cost-effective solutions to meet deadlines and deliver robust products.
• The Client-Facing Technologist: This persona acts as the crucial technical bridge between the data squad and the client. They build trust by listening actively, explaining complex data concepts (like data latency or idempotency) in simple terms, and demonstrating how engineering decisions align with the client’s strategic goals.
• The Quality Craftsman: This individual possesses an unwavering commitment to data integrity and treats data engineering as a craft. They are the guardian of the reporting layer, advocating for robust testing, data validation frameworks, and clean, modular code to ensure the long-term reliability of the data platform.

Experience & Relevance 

• Engineering Depth: 7-10 years of professional experience in end-to-end data product development. You have a portfolio that proves your ability to build complex, high-velocity pipelines for both Batch and Streaming workloads.
• Cloud-Native Fluency: Deep, hands-on experience designing and deploying scalable data solutions on at least one major cloud platform (AWS, GCP, or Azure). You are comfortable navigating the nuances of EMR, BigQuery, or Synapse at scale.
• AI-Native Workflow: You don’t just build for AI; you build with AI. You must be proficient in using AI coding assistants (e.g., GitHub Copilot) to accelerate your delivery and have a track record of building the data foundations required for Generative AI.
• Architectural Portfolio: Evidence of leading 2-3 large-scale transformations—including platform migrations, data lakehouse builds, or real-time analytics architectures.
• Client-Facing Acumen: You have direct experience in a consultative, client-facing role. You can confidently translate a CEO’s business vision into a Lead Engineer’s technical specification without losing anything in translation.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Director - Data engineering

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

what you will wake up to solve.

1. Delivery & Tactical Rigor

• Methodology Implementation: Implement and manage a unified, 'DataOps-First' methodology for data engineering delivery (ETL/ELT pipelines, Data Modeling, MLOps, Data Governance) within assigned business units. This ensures predictable outcomes and trusted data integrity by reducing architecture variability at the project level.
• Operational Stewardship: Drive initiatives to optimize team utilization and enhance operational efficiency within the practice. You manage the commercial success of your squads, ensuring data delivery models (from migration to modern data stack implementation) are executed profitably, scalably, and cost-effectively.
• Execution & Technical Resolution
• Technical Escalation: Serve as the primary escalation point for delivery issues, personally leading the resolution of complex data integration bottlenecks and pipeline failures to protect client timelines and data reliability standards.
• Quality Enforcement
• Quality Oversight: Execute and monitor technical data quality standards, ensuring engineering teams adhere to strict policies regarding data lineage, automated quality checks (observability), security/privacy compliance (GDPR/CCPA/PII), and active catalog management.

2. Strategic Growth & Practice Scaling

• Talent & Scaling Execution: Execute the strategy for data engineering talent acquisition and development within your business units. Implement objective metrics to assess and grow the 'Data-Native' DNA of your teams, ensuring squads are consistently equipped to handle petabyte-scale environments and high-impact delivery.
• Offerings Alignment: Drive the adoption of standardized regional offerings (e.g., Modern Data Platform, Data Mesh, Lakehouse Implementation). Ensure your teams leverage the profitable frameworks defined by the practice to accelerate time-to-insight and eliminate architectural fragmentation in client environments.
• Innovation & IP Development: Lead the practical integration of Vector Databases and LLM-ready architectures into project delivery. Champion the hands-on development of IP and reusable accelerators (e.g., automated ingestion engines) that improve delivery speed and enhance data availability across your portfolio.

3. Leadership & Unit Management

• Unit Leadership: Directly lead, mentor, and manage the Engineering Managers and Lead Architects within your business unit. Hold your teams accountable for project-level operational consistency, technical talent development, and strict adherence to the practice's data governance standards.
• Stakeholder Communication: Clearly articulate the business unit’s operational performance, technical quality metrics, and delivery progress to the C-suite Stakeholders and regional client leadership, bridging the gap between technical execution and business value.
• Ecosystem Alignment: Maintain strong technical relationships with key partner contacts (Snowflake, Databricks, AWS/GCP). Align team delivery capabilities with current product roadmaps and ensure squad-level participation in training, certifications, and partner-led enablement opportunities.

Welcome to Searce

The ‘process-first’, AI-native modern tech consultancy that's rewriting the rules.

We don’t do traditional.

As an engineering-led consultancy, we are dedicated to relentlessly improving the real business outcomes. Our solvers co-innovate with clients to futurify operations and make processes smarter, faster & better.

Functional Skills

1. Delivery Management & Operational Excellence

• Methodology Execution: Expert capability in implementing and enforcing a unified delivery methodology (DataOps, Agile, Mesh Principles) within specific business units. Proven track record of auditing squad-level adherence to ensure consistency across the project lifecycle.
• Operational Performance: High proficiency in managing day-to-day operational metrics, including squad utilization, resource forecasting, and productivity tracking. Skilled at optimizing team performance to meet profitability and efficiency targets.
• SOW & Risk Mitigation: Proven experience in operationalizing Statement of Work (SOW) requirements and identifying technical delivery risks early. Expert at mitigating scope creep and data-specific bottlenecks (e.g., latency, ingestion gaps) before they impact client outcomes.
• Technical Escalation Leadership: Demonstrated ability to lead "war room" efforts to resolve complex pipeline failures or data integrity issues. Skilled at providing clear, rapid remediation plans and communicating technical status directly to regional stakeholders.

2. Architectural Implementation & Technical Oversight

• Modern Stack Proficiency: Deep, hands-on expertise in implementing Cloud-Native architectures (Lakehouse, Data Mesh, MPP) on Snowflake, Databricks, or hyperscalers. Ability to conduct deep-dive architectural reviews and course-correct design decisions at the squad level to ensure scalability.
• Operationalizing Governance: Proven experience in embedding data quality and observability (completeness, freshness, accuracy) directly into the CI/CD pipeline. Responsible for technical enforcement of regulatory compliance (GDPR/PII) and maintaining the integrity of data catalogs across active projects.
• Applied Domain Expertise: Practical experience leading the delivery of high-growth solutions, specifically Generative AI infrastructure (RAG, Vector DBs), Real-Time Streaming, and large-scale platform migrations with a focus on zero-downtime execution.
• DataOps & Engineering Standards: Expert-level mastery of DataOps, including the setup and management of orchestration frameworks (Airflow, Dagster) and Infrastructure as Code (IaC). You ensure that automation is a baseline requirement, not an afterthought, for all delivery teams.

3. Unit Management & Commercial Execution

• Unit & Team Management: Proven success in leading and mentoring Engineering Managers and Lead Architects. Responsible for the operational metrics, technical output, and career development of the business unit's talent pool.
• Offerings Implementation & Scoping: Expertise in translating service offerings (e.g., Data Maturity Assessments, Lakehouse Builds) into accurate project scopes, technical estimates, and resource plans to ensure delivery is both profitable and competitive.
• Talent Growth & Mentorship: Functional ability to implement growth frameworks for data engineering roles. Focus on hands-on coaching and scaling high-performance technical talent to meet the demands of complex, petabyte-scale environments.
• Partner Enablement: Functional competence in managing regional technical relationships with major partners (Snowflake, Databricks, GCP/AWS). Drives squad-level certifications, joint technical enablement, and alignment with partner product roadmaps.

Tech Superpowers

• Modern Data Architect – Reimagines business with the Modern Data Stack (MDS) to deliver data mesh implementations, insights, & real value to clients.
• End-to-End Ecosystem Thinker – Builds modular, reusable data products across ingestion, transformation (ETL/ELT), governance, and consumption layers.
• Distributed Compute Savant – Crafts resilient, high-throughput architectures that survive petabyte-scale volume and data skew without breaking the bank.
• Governance & Integrity Guardian – Embeds data quality, complete lineage, and privacy-by-design (GDPR/PII) into every table, view, and pipeline.
• AI-Ready Orchestrator – Engineers pipelines that bridge structured data with Unstructured/Vector stores, powering RAG models and Generative AI workflows.
• Product-Minded Strategist – Balances architectural purity with time-to-insight; treats every dataset as a measurable "Data Product" with clear ROI.
• Pragmatic Stack Curator – Chooses the simplest tools that compound reliability; fluent in SQL, Python, Spark, dbt, and Cloud Warehouses.
• Builder @ Heart – Writes, reviews, and optimizes queries daily; proves architectures with cost-performance benchmarks, not slideware. Business-first, data-second, outcome focused technology leader.

Experience & Relevance

• Executive Experience: Minimum 10+ years of progressive experience in data engineering and analytics, with at least 3 years in a Senior Manager or Director -level role managing multiple technical teams and owning significant operational and efficiency metrics for a large data service line.
• Delivery Standardization: Demonstrated success in defining and implementing globally consistent, repeatable delivery methodologies (DataOps/Agile Data Warehousing) across diverse teams.
• Architectural Depth: Must retain deep, current expertise in Modern Data Stack architectures (Lakehouse, MPP, Mesh) and maintain the ability to personally validate high-level architectural and data pipeline design decisions.
• Operational Leadership: Proven expertise in managing and scaling large professional services organizations, demonstrated ability to optimize utilization, resource allocation, and operational expense.
• Domain Expertise: Strong background in Enterprise Data Platforms, Applied AI/ML, Generative AI integration, or large-scale Cloud Data Migration.
• Communication: Exceptional executive-level presentation and negotiation skills, particularly in communicating complex operational, data quality, and governance metrics to C-level stakeholders.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Solutions Architect - Data Engineering

Modern tech solutions advisory & 'futurify' consulting as a Searce lead fds (‘forward deployed solver’) architecting scalable data platforms and robust data engineering solutions that power intelligent insights and fuel AI innovation.

If you’re a tech-savvy, consultative seller with the brain of a strategist, the heart of a builder, and the charisma of a storyteller — we’ve got a seat for you at the front of the table.

You're not a sales lead. You're the transformation driver.

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

• Improver. Solver. Futurist.
• Great sense of humor.
• ‘Possible. It is.’ Mindset.
• Compassionate collaborator. Bold experimenter. Tireless iterator.
• Natural creativity that doesn’t just challenge the norm, but solves to design what’s better.
• Thinks in systems. Solves at scale.

This Isn’t for Everyone. But if you’re the kind who questions why things are done a certain way— and then identifies 3 better ways to do it — we’d love to chat with you.

Your Responsibilities

what you will wake up to solve.

You are not just a Solutions Architect; you are a futurifier of our data universe and the primary enabler of our AI ambitions. With a deep-seated passion for data engineering, you will architect and build the foundational data infrastructure that powers the customers entire data intelligence ecosystem.

As the Directly Responsible Individual (DRI) for our enterprise-grade data platforms, you own the outcome, end-to-end. You are the definitive solver for our customer's most complex data challenges, leveraging a powerful tech stack including Snowflake, Databricks, etc. and core GCP & AWS services (BigQuery, Spanner, Airflow, Kafka). This is a hands-on-keys role where you won't just design solutions—you'll build them, break them, and perfect them.

• Solution Design & Pre-sales Excellence:Collaborate with cross-functional teams, including sales, engineering, and operations, to ensure successful project delivery.
• Design Core Data Engineering: Master data modeling, architecting high-performance data ingestion pipelines and ensuring data quality and governance throughout the data lifecycle.
• Enable Cloud & AI: Design and implement solutions utilizing core GCP data services, building foundational data platforms that efficiently support advanced analytics and AI/ML initiatives.
• Optimize Performance & Cost: Continuously optimize data architectures and implementations for performance, efficiency, and cost-effectiveness within the cloud environment.
• Bridge Business & Tech: Translate complex business requirements into clear technical designs, providing technical leadership and guidance to data engineering teams.
• Stay Ahead of the Curve: Continuously research and evaluate new data technologies, architectural patterns, and industry trends to keep our data platforms at the cutting edge.

Functional Skills:

• Enterprise Data Architecture Design: Expert ability to design holistic, scalable, and resilient data architectures for complex enterprise environments.
• Cloud Data Platform Strategy: Proven capability to strategize, design, and implement cloud-native data platforms.
• Pre-Sales & Technical Storyteller: Crafts compelling, client-ready proposals, architectural decks, and technical demonstrations. Doesn't just present; shapes the strategic technical narrative behind every proposed solution.
• Advanced Data Modelling: Mastery in designing various data models for analytical, operational, and transactional use cases.
• Data Ingestion & Pipeline Orchestration: Strong expertise in designing and optimizing robust data ingestion and transformation pipelines.
• Stakeholder Communication: Exceptional skills in articulating complex technical concepts and architectural decisions to both technical and non-technical stakeholders.
• Performance & Cost Optimization: Adept at optimizing data solutions for performance, efficiency, and cost within a cloud environment.

Tech Superpowers:

• Cloud Data Mastery: You're a wizard at leveraging public cloud data services, with deep expertise in GCP (BigQuery, Spanner, etc.) and expert proficiency in modern data warehouse solutions like Snowflake.
• Data Engineering Core: Highly skilled in designing, implementing, and managing data workflows using tools like Apache Airflow and Apache Kafka. You're also an authority on advanced data modeling and ETL/ELT patterns.
• AI/ML Data Foundation: You instinctively design data pipelines and structures that efficiently feed and empower Machine Learning and Artificial Intelligence applications.
• Programming for Data: You have a strong command over key programming languages (Python, SQL) for scripting, automation, and building data processing applications.

Experience & Relevance:

• Architectural Leadership (8+ Years): You bring extensive experience (7+ years) specifically in a Solutions Architect role, focused on data engineering and platform building.
• Cloud Data Expertise: You have a proven track record of designing and implementing production-grade data solutions leveraging major public cloud platforms, with significant experience in Google Cloud Platform (GCP).
• Data Warehousing & Data Platform: Demonstrated hands-on experience in the end-to-end design, implementation, and optimization of modern data warehouses and comprehensive data platforms.
• Databricks & BigQuery Mastery: You possess significant practical experience with Databricks as a core data warehouse and GCP BigQuery for analytical workloads.
• Data Ingestion & Orchestration: Proven experience designing and implementing complex data ingestion pipelines and workflow orchestration using tools like Airflow and real-time streaming technologies like Kafka.
• AI/ML Data Enablement: Experience in building data foundations specifically geared towards supporting Machine Learning and Artificial Intelligence initiatives.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’.

Don’t Just Send a Resume. Send a Statement.

So, If you are passionate about tech, future & what you read above (we really are!), apply here to experience the ‘Art of Possible’

Responsibilities

• Technical Leadership & Architecture: Serve as a technical authority, define cloud-native standards, and own end-to-end system design for complex, distributed, and high-scale solutions.
• Engineering Excellence: Lead modernization initiatives, transition legacy systems to microservices, and ensure performance, scalability, and security.
• Platform & Cloud Enablement: Champion GCP-native services (GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL, Spanner), influence CI/CD, and drive FinOps strategies.
• Mentorship & Organizational Impact: Mentor Lead and Senior Engineers, foster engineering rigor, and collaborate with Product Management to translate business strategy into technical solutions.

Required Skills, Experience & Background

• 12+ years of professional experience building enterprise-grade software systems.
• Proven experience operating at a Lead or Principal Engineer level.
• Strong hands-on experience with Java or another major programming language (e.g., Go, Python, C#).
• Deep expertise in microservices architecture, RESTful APIs, and distributed systems.
• Strong experience with SQL and NoSQL databases and data modeling.
• Expertise in cloud-native design principles (stateless services, scalability, resiliency).
• Strong experience building and operating systems on Google Cloud Platform (GCP).
• Proficiency with containers and orchestration (Docker, Kubernetes, GKE).
• Experience with CI/CD pipelines, Git-based workflows, and observability.
• Experience with Big Data and data engineering technologies (e.g., BigQuery, Spark).

Qualifications

• Bachelor’s degree in computer science or related field (required).
• Master’s degree in computer science or related field (preferred).

Key Responsibilities:

• Lead and mentor a team of Java and Python developers, providing technical guidance and fostering a culture of continuous learning and improvement.
• Oversee the design, development, and implementation of high-performance, scalable, and secure software solutions for the financial services industry.
• Collaborate with product managers and architects to translate business requirements into technical specifications and ensure alignment with overall product strategy.
• Drive the adoption of best practices in software development, including code reviews, testing, and continuous integration/continuous deployment (CI/CD).
• Manage project timelines and resources effectively, ensuring on-time and within-budget delivery of projects.
• Identify and mitigate technical risks, proactively addressing potential issues and ensuring the stability and reliability of our platforms.
• Stay abreast of emerging technologies and trends in Java, Python, and related fields, and evaluate their potential application to our products and services.
• Contribute to the development of technical documentation and training materials.

Required Skillset:

• Demonstrated expertise in Java and Python development, with a strong understanding of object-oriented principles, design patterns, and data structures.
• Proven ability to lead and mentor a team of software engineers, fostering a collaborative and high-performing environment.
• Experience in designing and developing scalable, high-performance, and secure software solutions.
• Strong understanding of software development methodologies, including Agile and Waterfall.
• Excellent communication, interpersonal, and problem-solving skills.
• Ability to work effectively in a fast-paced, dynamic environment.
• Bachelor's or Master's degree in Computer Science or a related field.
• Experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) is a plus.

Job Summary: 

We are looking for an experienced GCP Cloud Engineer to design, implement, and manage cloud-based solutions on Google Cloud Platform (GCP). The ideal candidate should have expertise in GKE (Google Kubernetes Engine), Cloud Run, Cloud Loadbalancer, Cloud function, Azure DevOps, and Terraform, with a strong focus on automation, security, and scalability. 

You will work closely with development, operations, and security teams to ensure robust cloud infrastructure and CI/CD pipelines while optimizing performance and cost. 

Key Responsibilities: 

1. Cloud Infrastructure Design & Management 

• Architect, deploy, and maintain GCP cloud resources via terraform/other automation. 
• Implement Google Cloud Storage, Cloud SQL, filestore, for data storage and processing needs. 
• Manage and configure Cloud Load Balancers (HTTP(S), TCP/UDP, and SSL Proxy) for high availability and scalability. 
• Optimize resource allocation, monitoring, and cost efficiency across GCP environments. 

2. Kubernetes & Container Orchestration 

• Deploy, manage, and optimize workloads on Google Kubernetes Engine (GKE). 
• Work with Helm charts for microservices deployments. 
• Automate scaling, rolling updates, and zero-downtime deployments. 

3. Serverless & Compute Services 

• Deploy and manage applications on Cloud Run and Cloud Functions for scalable, serverless workloads. 
• Optimize containerized applications running on Cloud Run for cost efficiency and performance. 

4. CI/CD & DevOps Automation 

• Design, implement, and manage CI/CD pipelines using Azure DevOps. 
• Automate infrastructure deployment using Terraform, Bash and Powershell scripting 
• Integrate security and compliance checks into the DevOps workflow (DevSecOps). 

Required Skills & Qualifications: 

✔ Experience: 4+ years in Cloud Engineering, with a focus on GCP. 

✔ Cloud Expertise: Strong knowledge of GCP services (GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Functions). 

✔ Kubernetes & Containers: Experience with GKE, Docker, GKE Networking, Helm. 

✔ DevOps Tools: Hands-on experience with Azure DevOps for CI/CD pipeline automation. 

✔ Infrastructure-as-Code (IaC): Expertise in Terraform for provisioning cloud resources. 

✔ Scripting & Automation: Proficiency in Python, Bash, or PowerShell for automation. 

✔ Security & Compliance: Knowledge of cloud security principles, IAM, and compliance standards. 

DevOps Engineer

Location: Bangalore office

About Peliqan

Peliqan is an all-in-one data platform combining ELT/ETL pipelines, a built-in data warehouse, SQL and low-code Python transformations, reverse ETL, and AI-powered data activation. We connect 250+ data sources and serve enterprise teams, consultants, and SaaS companies. SOC 2 Type II certified and GDPR compliant.

The Role

Own and evolve the infrastructure powering Peliqan's multi-tenant data platform. You'll manage Kubernetes clusters, cloud resources, CI/CD pipelines, and monitoring — keeping everything reliable, secure, and scalable. You'll be the go-to person for infrastructure support across the engineering team.

Responsibilities

Manage and optimise Kubernetes clusters running production workloads — data pipelines, APIs, and customer-facing services.

Maintain Docker-based local development environments for the engineering team.

Administer cloud infrastructure on AWS and Google Cloud (compute, storage, networking, managed databases).

Build and maintain CI/CD pipelines for automated testing, building, and deploying across staging and production.

Set up and manage monitoring, alerting, and logging for platform health and incident response.

Manage release processes — deployments, rollbacks, and release strategies.

• Maintain infrastructure-as-code using Helm charts.
• Support security hardening and compliance efforts (SOC 2, GDPR).

Requirements

3+ years in a DevOps, SRE, or Infrastructure Engineering role.

Strong hands-on experience with Kubernetes and Helm charts.

Deep familiarity with Docker for containerisation and local dev workflows.

Production experience with AWS and/or Google Cloud.

• Proficiency in Python and Bash scripting for automation and tooling.
• Solid grasp of DevOps principles: infrastructure-as-code, GitOps, observability, continuous delivery.
• Experience with CI/CD platforms (GitHub Actions, GitLab CI, or similar).

Nice to Have

• Experience supporting multi-tenant SaaS platforms or data infrastructure at scale.
• Knowledge of PostgreSQL, MySQL, or cloud-managed database administration.
• Exposure to security compliance frameworks (SOC 2, ISO 27001, GDPR).

Job Description - Manager Sales

Min 15 years experience,

Should be experience from Sales of Cloud IT Saas Products portfolio which Savex deals with,

Team Management experience, leading cloud business including teams

Sales manager - Cloud Solutions

Reporting to Sr Management

Good personality

Distribution backgroung

Keen on Channel partners

Good database of OEMs and channel partners.

Age group - 35 to 45yrs

Male Candidate

Good communication

B2B Channel Sales

Location - Bangalore

If interested reply with cv and below details

Total exp -

Current ctc - 

Exp ctc - 

Np -

Current location - 

Qualification - 

Total exp Channel Sales -

What are the Cloud IT products, you have done sales for? 

What is the Annual revenue generated through Sales ?

Role & Responsibilities:

We are looking for a strong Data Engineer to join our growing team. The ideal candidate brings solid ETL fundamentals, hands-on pipeline experience, and cloud platform proficiency — with a preference for GCP / BigQuery expertise.

Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows
• Work with Dataform or DBT to implement transformation logic and data models
• Develop and optimize data solutions on GCP (BigQuery, GCS) or AWS/Azure
• Support data migration initiatives and data mesh architecture patterns
• Collaborate with analysts, scientists, and business stakeholders to deliver reliable data products
• Apply data governance and quality best practices across the data lifecycle
• Troubleshoot pipeline issues and drive proactive monitoring and resolution

Ideal Candidate:

• Strong Data Engineer Profile
• Must have 6+ years of hands-on experience in Data Engineering, with strong ownership of end-to-end data pipeline development.
• Must have strong experience in ETL/ELT pipeline design, transformation logic, and data workflow orchestration.
• Must have hands-on experience with any one of the following: Dataform, dbt, or BigQuery, with practical exposure to data transformation, modeling, or cloud data warehousing.
• Must have working experience on any cloud platform: GCP (preferred), AWS, or Azure, including object storage (GCS, S3, ADLS).
• Must have strong SQL skills with experience in writing complex queries and optimizing performance.
• Must have programming experience in Python and/or SQL for data processing.
• Must have experience in building and maintaining scalable data pipelines and troubleshooting data issues.
• Exposure to data migration projects and/or data mesh architecture concepts.
• Experience with Spark / PySpark or large-scale data processing frameworks.
• Experience working in product-based companies or data-driven environments.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

NOTE:

• There will be an interview drive scheduled on 28th and 29th March 2026, and if shortlisted, they will be expected to be available on these Interview dates. Only Immediate joiners are considered.

🚨 We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Own and evolve the technical backbone of an AI-first enterprise platform.

You will define architecture across LLM-powered systems, distributed services, and data platforms — and lead critical transformations from legacy → AI-native systems.

🧩 What You’ll Do

• Architect large-scale distributed systems powering AI-driven workflows
• Lead 0→1 and 1→N platform builds (LLM integrations, agentic systems, orchestration layers)
• Redesign legacy systems into scalable, modular, AI-native architectures
• Drive system design excellence across teams (APIs, infra, observability, reliability)
• Make high-stakes decisions on trade-offs (latency, cost, scalability, model performance)
• Mentor senior engineers and influence engineering culture/org standards
• Partner with product, data, and leadership on long-term technical strategy

🧠 What We’re Looking For

• Proven track record building high-scale backend or platform systems
• Deep expertise in distributed systems, microservices, cloud (AWS/GCP/Azure)
• Strong exposure to data systems/infra / Data / real-time architectures
• Experience or strong interest in LLMs, GenAI, or AI system design
• Exceptional system design, abstraction, and problem-solving ability
• High ownership mindset — you think in terms of systems, not tickets
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset
• Solve hard system problems (latency, scale, reliability)
• Drive cross-team technical decisions and standards
• Mentor senior engineers and influence org-wide architecture 
• Design large-scale distributed systems and backend platforms
• Mentorship & Technical Leadership 
• Expertise in system design, scalability, and performance optimization

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Job Details

- Job Title: Full Stack Engineer

- Industry: SAAS

- Function – Information Technology

- Experience Required: 5-7 years

- Working Days: 6 days

- Employment Type: Full Time

- Job Location: Bangalore

- CTC Range: Best in Industry

Preferred Skills: TypeScript, NodeJS, mongodb, RESTful APIs, React.js

Criteria

Candidate should have at least 4+ years of professional experience as a Full Stack Engineer

Hands-on experience with both React.js and Node.js

Solid understanding of MongoDB

Should have experience in RESTful APIs

Should be from a startup or scale up companies

Should have good experience in Typescript

Strong understanding of asynchronous programming patterns

Preferred candidates from SAAS/Software/IT Services based startups or scaleup companies

Job Description

The Role:

We’re looking for a Full Stack Engineer to build, scale, and maintain high-performance web applications for company’s technology platforms. This role involves working across the stack-frontend, backend, and infrastructure - using modern JavaScript-based technologies.

You’ll collaborate closely with product managers, designers, and cross-functional engineering teams to deliver scalable, secure, and user-centric solutions. This role is ideal for someone who enjoys end-to-end ownership, technical problem-solving, and working in a fast-paced startup environment.

What You’ll Own

1. Full Stack Development

● Design, develop, test, and deploy robust and scalable web applications.

● Build and maintain server-side logic and microservices using Node.js, Express.js, and TypeScript.

● Contribute to frontend feature development and integration.

● Participate in feature planning, estimation, and execution.

2. Backend & API Engineering

● Design and develop RESTful APIs and backend services.

● Implement asynchronous workflows and scalable microservice architectures.

● Ensure performance, reliability, and security of backend systems.

● Implement authentication, authorization, and data protection best practices.

3. Database Design & Optimization

● Design and manage MongoDB schemas using Mongoose.

● Optimize queries and database performance for scale.

● Ensure data integrity and efficient data access patterns.

4. Frontend Collaboration & Integration

● Collaborate with frontend developers to integrate React components and APIs seamlessly.

● Ensure responsive, high-performing application behavior.

5. System Design & Scalability

● Contribute to system architecture and technical design discussions.

● Design scalable, maintainable, and future-ready solutions.

● Optimize applications for speed and scalability.

6. Product & Cross-Functional Collaboration

● Work closely with product and design teams to deliver high-quality features in rapid iterations.

● Participate in the full development lifecycle—from concept to deployment and maintenance.

7. Code Quality & Best Practices

● Write clean, testable, and maintainable code.

● Follow Git-based version control and code review best practices.

● Contribute to improving engineering standards and workflows.

What We’re Looking For

Must-Haves

● 4+ years of professional experience as a Full Stack Engineer or similar role.

● Strong proficiency in JavaScript and TypeScript.

● Hands-on experience with Node.js and Express.js.

● Solid understanding of MongoDB and Mongoose.

● Experience building and consuming RESTful APIs and microservices.

● Strong understanding of asynchronous programming patterns.

● Good grasp of system design principles and application architecture.

● Experience with Git and version control best practices.

● Bachelor’s degree in Computer Science, Engineering, or a related field.

Good-to-Have / Preferred

● Frontend development experience with React.js.

● Exposure to Three.js or similar 3D/visualization libraries.

● Experience with cloud platforms (AWS, GCP, Azure – EC2, S3, Lambda).

● Knowledge of Docker and containerization workflows.

● Experience with testing frameworks (Jest, Mocha, etc.).

● Familiarity with CI/CD pipelines and automated deployments.

Tools You’ll Use

● Backend: Node.js, Express.js, TypeScript

● Frontend: React.js (preferred)

● Database: MongoDB, Mongoose

● Version Control: Git, GitHub / GitLab

● Cloud & DevOps: AWS / GCP / Azure, Docker

● Collaboration: Google Workspace, Notion, Slack

Key Metrics You’ll Own

● Code quality, performance, and scalability

● Timely delivery of features and releases

● System reliability and reduction in production issues

● Contribution to architectural improvements

Why company

● Work on impactful, product-driven tech platforms.

● High-ownership role with end-to-end engineering exposure.

● Opportunity to work with modern technologies and evolving architectures.

● Collaborative startup culture with strong learning and growth opportunities.

Job Details

- Job Title: Senior Backend Engineer

- Industry: SAAS

- Function – Information Technology

- Experience Required: 5-8 years

- Working Days: 6 days a week, (5 days-in-office, Saturdays WFH)

- Employment Type: Full Time

- Job Location: Bangalore

- CTC Range: Best in Industry

Preferred Skills: AWS, NodeJS, RESTful APIs, NoSQL

Criteria

· Minimum 5+ years in backend engineering with strong system design expertise

· Experience building scalable systems from scratch

· Expert-level proficiency in Node.js

· Deep understanding of distributed systems

· Strong NoSQL design skills

· Hands-on AWS cloud experience

· Proven leadership and mentoring capability

· Preferred candidates from SAAS/Software/IT Services based startups or scaleup companies

Job Description

The Role:

What You’ll Build:

1. System Architecture & Design

● Architect highly scalable backend systems from the ground up

● Define technology choices: frameworks, databases, queues, caching layers

● Evaluate microservices vs monoliths based on product stage

● Design REST, GraphQL, and real-time WebSocket APIs

● Build event-driven systems for asynchronous processing

● Architect multi-tenant systems with strict data isolation

● Maintain architectural documentation and technical specs

2. Core Backend Services

● Build high-performance APIs for 3D content, XR experiences, analytics, and user interactions

● Create 3D asset processing pipelines for uploads, conversions, and optimization

● Develop distributed job workers for CPU/GPU-intensive tasks

● Build authentication/authorization systems (RBAC)

● Implement billing, subscription, and usage metering

● Build secure webhook systems and third-party integration APIs

● Create real-time collaboration features via WebSockets/SSE

3. Data Architecture & Databases

● Design scalable schemas for 3D metadata, XR sessions, and analytics

● Model complex product catalogs with variants and hierarchies

● Implement Redis-based caching strategies

● Build search and indexing systems (Elasticsearch/Algolia)

● Architect ETL pipelines and data warehouses

● Implement sharding, partitioning, and replication strategies

● Design backup, restore, and disaster recovery workflows

4. Scalability & Performance

● Build systems designed for 10x–100x traffic growth

● Implement load balancing, autoscaling, and distributed processing

● Optimize API response times and database performance

● Implement global CDN delivery for heavy 3D assets

● Build rate limiting, throttling, and backpressure mechanisms

● Optimize storage and retrieval of large 3D files

● Profile and improve CPU, memory, and network performance

5. Infrastructure & DevOps

● Architect AWS infrastructure (EC2, S3, Lambda, RDS, ElastiCache)

● Build CI/CD pipelines for automated deployments and rollbacks

● Use IaC tools (Terraform/CloudFormation) for infra provisioning

● Set up monitoring, logging, and alerting systems

● Use Docker + Kubernetes for container orchestration

● Implement security best practices for data, networks, and secrets

● Define disaster recovery and business continuity plans

6. Integration & APIs

● Build integrations with Shopify, WooCommerce, Magento

● Design webhook systems for real-time events

● Build SDKs, client libraries, and developer tools

● Integrate payment gateways (Stripe, Razorpay)

● Implement SSO and OAuth for enterprise customers

● Define API versioning and lifecycle/deprecation strategies

7. Data Processing & Analytics

● Build analytics pipelines for engagement, conversions, and XR performance

● Process high-volume event streams at scale

● Build data warehouses for BI and reporting

● Develop real-time dashboards and insights systems

● Implement analytics export pipelines and platform integrations

● Enable A/B testing and experimentation frameworks

● Build personalization and recommendation systems

Technical Stack:

1. Backend Languages & Frameworks 

●  Primary: Node.js (Express, NestJS), Python (FastAPI, Django)

●  Secondary: Go, Java/Kotlin (Spring)

●  APIs: REST, GraphQL, gRPC

2. Databases & Storage

● SQL: PostgreSQL, MySQL

● NoSQL: MongoDB, DynamoDB

● Caching: Redis, Memcached

● Search: Elasticsearch, Algolia

● Storage/CDN: AWS S3, CloudFront

● Queues: Kafka, RabbitMQ, AWS SQS

3. Cloud & Infrastructure: 

● Cloud: AWS (primary), GCP/Azure (nice to have)

● Compute: EC2, Lambda, ECS, EKS

● Infrastructure: Terraform, CloudFormation

● CI/CD: GitHub Actions, Jenkins, CircleCI

● Containers: Docker, Kubernetes

4. Monitoring & Operations 

● Monitoring: Datadog, New Relic, CloudWatch

● Logging: ELK Stack, CloudWatch Logs

● Error Tracking: Sentry, Rollbar

● APM tools

5. Security & Auth

● Auth: JWT, OAuth 2.0, SAML

● Secrets: AWS Secrets Manager, Vault

● Security: Encryption (at rest/in transit), TLS/SSL, IAM

What We’re Looking For:

1. Must-Haves

● 5+ years in backend engineering with strong system design expertise

● Experience building scalable systems from scratch

● Expert-level proficiency in at least one backend stack (Node, Python, Go, Java)

● Deep understanding of distributed systems and microservices

● Strong SQL/NoSQL design skills with performance optimization

● Hands-on AWS cloud experience

● Ability to write high-quality production code daily

● Experience building and scaling RESTful APIs

● Strong understanding of caching, sharding, horizontal scaling

● Solid security and best-practice implementation experience

● Proven leadership and mentoring capability

2. Highly Desirable

● Experience with large file processing (3D, video, images)

● Background in SaaS, multi-tenancy, or e-commerce

● Experience with real-time systems (WebSockets, streams)

● Knowledge of ML/AI infrastructure

● Experience with HA systems, DR planning

● Familiarity with GraphQL, gRPC, event-driven systems

● DevOps/infrastructure engineering background

● Experience with XR/AR/VR backend systems

● Open-source contributions or technical writing

● Prior senior technical leadership experience

Technical Challenges You’ll Solve:

● Designing large-scale 3D asset processing pipelines

● Serving XR content globally with ultra-low latency

● Scaling from thousands to millions of daily requests

● Efficiently handling CPU/GPU-heavy workloads

● Architecting multi-tenancy with complete data isolation

● Managing billions of analytics events at scale

● Building future-proof APIs with backward compatibility

Why company:

● Architectural Ownership: Build foundational systems from scratch

● Deep Technical Work: Solve distributed systems and scaling challenges

● Hands-On Impact: Design and code mission-critical infrastructure

● Diverse Problems: APIs, infra, data, ML, XR, asset processing

● Massive Scale Opportunity: Build systems for exponential growth

● Modern Stack and best practices

● Product Impact: Your architecture directly powers millions of users

● Leadership Opportunity: Shape engineering culture and direction

● Learning Environment: Stay at the forefront of backend engineering

● Backed by AWS, Microsoft, Google

Location & Work Culture:

● Location: Bengaluru

● Schedule: 6 days a week, (5 days-in-office, Saturdays WFH)

● Culture: Builder mindset, strong ownership, technical excellence

● Team: Small, highly skilled backend and infra team

● Resources: AWS credits, latest tooling, learning budget

Job Description:

We are seeking a Cloud & AI Platform Engineer to design and operate AI-native infrastructure that supports large-scale machine learning, generative AI, and agentic AI systems. 

This role will focus on building secure, scalable, and automated multi-cloud platforms across AWS, Azure, GCP, and hybrid on-prem environments, enabling teams to deploy LLMs, AI agents, and data-driven applications reliably in production. 

You will work at the intersection of cloud engineering, MLOps, LLMOps, DevOps, and data infrastructure, helping build platforms that support RAG pipelines, vector search, AI model lifecycle management, and AI observability. 

Key Responsibilities

AI & Agentic Infrastructure 

• Design infrastructure to support agentic AI systems, autonomous agents, and multi-agent workflows. 
• Build scalable runtime environments for LLM orchestration frameworks. 
• Enable deployment of AI copilots, assistants, and autonomous decision systems. 

Common frameworks may include: 

• LangChain 
• LlamaIndex 
• AutoGPT 

LLMOps & AI Model Lifecycle 

Design and manage LLMOps pipelines for the full lifecycle of large language models: 

• Model deployment 
• Prompt management 
• Versioning 
• Evaluation and testing 
• Model monitoring 

Integrate with AI platforms such as: 

• Azure Machine Learning 
• Amazon SageMaker 
• Vertex AI 

Retrieval-Augmented Generation (RAG) Infrastructure 

Design and optimize RAG pipelines that integrate enterprise knowledge with LLMs. 

Responsibilities include: 

• Document ingestion pipelines 
• Embedding generation workflows 
• Knowledge indexing 
• Query orchestration 
• Retrieval optimization 
• Support scalable semantic search architectures. 

Vector Database & Knowledge Infrastructure 

Deploy and manage vector databases used for AI applications and semantic retrieval. 

Common technologies include: 

• Pinecone 
• Weaviate 
• Milvus 
• FAISS 

Responsibilities include: 

• Index optimization 
• Query latency tuning 
• Scalable embedding storage 
• Hybrid search architecture 

Multi-Cloud AI Infrastructure 

Design and maintain AI-ready infrastructure across: 

• Amazon Web Services 
• Microsoft Azure 
• Google Cloud Platform 

Key responsibilities include: 

• GPU infrastructure management 
• Distributed training environments 
• Hybrid cloud integrations with on-prem data centers 
• Infrastructure scaling for AI workloads 

Data Platforms & Integration 

• Support deployment and optimization of data lakes, data warehouses, and streaming platforms. 
• Work with data engineering teams to ensure secure and scalable data infrastructure. 

Cloud Architecture & Infrastructure 

• Design and implement scalable multi-cloud infrastructure across Azure, AWS, and Google Cloud. 
• Build hybrid cloud architectures integrating on-premise environments with cloud platforms. 
• Implement high availability, disaster recovery, and auto-scaling architectures for AI workloads. 

DevOps, Platform Engineering & Automation 

Build automated cloud infrastructure using modern DevOps practices. 

Tools may include: 

• Terraform 
• Docker 
• Kubernetes 
• GitHub Actions 

Responsibilities include: 

• Infrastructure as Code (IaC) 
• Automated deployments 
• CI/CD pipelines for AI models and services 
• Platform reliability and scalability 

AI Observability & Monitoring 

Implement observability frameworks to monitor AI systems in production. 

This includes: 

• Model performance monitoring 
• Prompt evaluation 
• Hallucination detection 
• Latency and throughput analysis 
• Cost monitoring for LLM usage 

Tools may include: 

• Arize AI 
• WhyLabs 
• Weights & Biases 

Security, Governance & Responsible AI 

Ensure AI systems follow strong governance and security practices. 

Responsibilities include: 

• Data privacy and compliance 
• Model governance frameworks 
• Secure model deployment 
• Monitoring model bias and drift 
• AI risk management 

Support enterprise frameworks for Responsible AI and AI compliance. 

Data & Security 

• Experience with data lake architectures, distributed storage, and ETL pipelines 
• Knowledge of data security, encryption, IAM, and compliance frameworks 
• Familiarity with AI governance and responsible AI practices 

Required Skills 

Cloud & Infrastructure 

• Strong experience in Azure (must have), AWS or GCP 
• Hybrid and multi-cloud architecture 
• GPU infrastructure management 

DevOps & Automation 

• Kubernetes 
• Docker 
• Terraform 
• CI/CD pipelines 

AI / ML Platforms 

• MLOps pipelines 
• Model deployment 
• Model monitoring 

AI Application Infrastructure 

• Vector databases 
• RAG pipelines 
• LLM orchestration frameworks 

Programming 

Experience in one or more languages: 

• Python 
• Go 
• Java 
• TypeScript 

Preferred Qualifications 

• Experience building AI copilots or autonomous agents 
• Knowledge of distributed model training - Knowledge of GPU infrastructure and distributed training 
• Familiarity with AI evaluation frameworks - Familiarity with model monitoring, drift detection, and AI observability 
• Experience building enterprise AI platforms 

Education & Experience 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 
• 4–8+ years experience in cloud infrastructure, DevOps, or platform engineering 
• Experience working in data-driven or AI-focused environments 

What Success Looks Like 

• Reliable ML model deployment pipelines - Reliable infrastructure for LLMs and AI agents, Scalable RAG knowledge platforms 
• Efficient multi-cloud infrastructure management - Fast deployment cycles for AI products 
• Secure and scalable AI-ready cloud platforms 
• Strong automation and governance across cloud and AI systems 

Job Title: Account Manager – USA Market

Experience: 3–8 Years

Department: Sales

US Market experience mandatory

Any gender

Shift timing: 6 PM to 3 AM

Max CTC: 15 LPA(both position)

Inhouse desk job

Individual Contributor role

B2B SaaS Company Experience Mandatory

5 days of working from the office.

Role Overview

We are seeking a results-driven Account Manager to manage and grow client relationships in the

U.S. market, with a strong preference for candidates with experience in cloud migration services.

The ideal candidate will have a proven track record in B2B sales, account growth, and consultative selling within IT services or cloud solutions.

You will be responsible for managing existing accounts, identifying expansion opportunities, driving

revenue growth, and positioning cloud migration solutions (M365/Azure/GCP) that align with client

business objectives.

Key Responsibilities

 Manage and grow assigned accounts within the USA market.

 Act as the primary point of contact for client stakeholders.

 Identify upsell and cross-sell opportunities, particularly in:

o Cloud migration & modernization

o Infrastructure transformation

o Managed cloud services

 Drive end-to-end sales cycles from requirement gathering to deal closure.

 Collaborate with pre-sales, cloud architects, and delivery teams to craft tailored cloud migration solutions.

 Build long-term relationships with CXOs, IT Directors, and decision-makers.

 Prepare account plans, revenue forecasts, and pipeline reports.

 Meet and exceed quarterly and annual revenue targets.

 Negotiate commercial terms and manage contract renewals.

 Stay up to date with cloud trends, competitive landscape, and US market dynamics.

Required Qualifications

 3–8 years of experience in: Account management / IT services sales / technology consulting

o Handling USA clients (mandatory)

 Proven experience selling cloud solutions and/or IT services.

 Understanding of:

o M365, Azure, or Google Cloud platforms

o Cloud migration strategies (lift & shift, re-platform, re-architect)

o Application modernization & ; infrastructure services

 Strong consultative selling and negotiation skills.

 Experience managing multi-million-dollar accounts (preferred).

 Excellent communication and presentation skills.

 Ability to work in US time zones as required.

About the role:

We are looking for a skilled and driven Security Engineer to join our growing security team. This role requires a hands-on professional who can evaluate and strengthen the security posture of our

applications and infrastructure across Web, Android, iOS, APIs, and cloud-native environments.

The ideal candidate will also lead technical triage from our bug bounty program, integrate security into the DevOps lifecycle, and contribute to building a security-first engineering culture.

Required Skills & Experience:

● 3 to 6 years of solid hands-on experience in the VAPT domain

● Solid understanding of Web, Android, and iOS application security

● Experience with DevSecOps tools and integrating security into CI/CD

● Strong knowledge of cloud platforms (AWS/GCP/Azure) and their security models

● Familiarity with bug bounty programs and responsible disclosure practices

● Familiarity with tools like Burp Suite, MobSF, OWASP ZAP, Terraform, Checkov..etc

● Good knowledge of API security

● Scripting experience (Python, Bash, or similar) for automation tasks

Preferred Qualifications:

● OSCP, CEH, AWS Security Specialty, or similar certifications

● Experience working in a regulated environment (e.g., FinTech, InsurTech)

Responsibilities:

● Perform Security reviews, Vulnerability Assessments & Penetration Testing for Web,

Android, iOS, and API endpoints

● Perform Threat Modelling & anticipate potential attack vectors and improve security

architecture on complex or cross-functional components

● Identify and remediate OWASP Top 10 and mobile-specific vulnerabilities

● Conduct secure code reviews and red team assessments

● Integrate SAST, DAST, SCA, and secret scanning tools into CI/CD pipelines

● Automate security checks using tools like SonarQube, Snyk, Trivy, etc.

● Maintain and manage vulnerability scanning infrastructure

● Perform security assessments of AWS, Azure, and GCP environments, with an emphasis

on container security, particularly for Docker and Kubernetes.

● Implement guardrails for IAM, network segmentation, encryption, and cloud monitoring

● Contribute to infrastructure hardening for containers, Kubernetes, and virtual machines

● Triage bug bounty reports and coordinate remediation with engineering teams

● Act as the primary responder for external security disclosures

● Maintain documentation and metrics related to bug bounty and penetration testing

activities

● Collaborate with developers and architects to ensure secure design decisions

● Lead security design reviews for new features and products

● Provide actionable risk assessments and mitigation plans to stakeholders

JOB DETAILS:

* Job Title: Principal Data Scientist

* Industry: Healthcare

* Salary: Best in Industry

* Experience: 6-10 years

* Location: Bengaluru

Preferred Skills: Generative AI, NLP & ASR, Transformer Models, Cloud Deployment, MLOps

Criteria:

1. Candidate must have 7+ years of experience in ML, Generative AI, NLP, ASR, and LLMs (preferably healthcare).
2. Candidate must have strong Python skills with hands-on experience in PyTorch/TensorFlow and transformer model fine-tuning.
3. Candidate must have experience deploying scalable AI solutions on AWS/Azure/GCP with MLOps, Docker, and Kubernetes.
4. Candidate must have hands-on experience with LangChain, OpenAI APIs, vector databases, and RAG architectures.
5. Candidate must have experience integrating AI with EHR/EMR systems, ensuring HIPAA/HL7/FHIR compliance, and leading AI initiatives.

Job Description

Principal Data Scientist

(Healthcare AI | ASR | LLM | NLP | Cloud | Agentic AI)

Job Details

• Designation: Principal Data Scientist (Healthcare AI, ASR, LLM, NLP, Cloud, Agentic AI)
• Location: Hebbal Ring Road, Bengaluru
• Work Mode: Work from Office
• Shift: Day Shift
• Reporting To: SVP
• Compensation: Best in the industry (for suitable candidates)

Educational Qualifications

• Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• Technical certifications in AI/ML, NLP, or Cloud Computing are an added advantage

Experience Required

• 7+ years of experience solving real-world problems using:
• Natural Language Processing (NLP)
• Automatic Speech Recognition (ASR)
• Large Language Models (LLMs)
• Machine Learning (ML)
• Preferably within the healthcare domain
• Experience in Agentic AI, cloud deployments, and fine-tuning transformer-based models is highly desirable

Role Overview

This position is part of company, a healthcare division of Focus Group specializing in medical coding and scribing.

We are building a suite of AI-powered, state-of-the-art web and mobile solutions designed to:

• Reduce administrative burden in EMR data entry
• Improve provider satisfaction and productivity
• Enhance quality of care and patient outcomes

Our solutions combine cutting-edge AI technologies with live scribing services to streamline clinical workflows and strengthen clinical decision-making.

The Principal Data Scientist will lead the design, development, and deployment of cognitive AI solutions, including advanced speech and text analytics for healthcare applications. The role demands deep expertise in generative AI, classical ML, deep learning, cloud deployments, and agentic AI frameworks.

Key Responsibilities

AI Strategy & Solution Development

• Define and develop AI-driven solutions for speech recognition, text processing, and conversational AI
• Research and implement transformer-based models (Whisper, LLaMA, GPT, T5, BERT, etc.) for speech-to-text, medical summarization, and clinical documentation
• Develop and integrate Agentic AI frameworks enabling multi-agent collaboration
• Design scalable, reusable, and production-ready AI frameworks for speech and text analytics

Model Development & Optimization

• Fine-tune, train, and optimize large-scale NLP and ASR models
• Develop and optimize ML algorithms for speech, text, and structured healthcare data
• Conduct rigorous testing and validation to ensure high clinical accuracy and performance
• Continuously evaluate and enhance model efficiency and reliability

Cloud & MLOps Implementation

• Architect and deploy AI models on AWS, Azure, or GCP
• Deploy and manage models using containerization, Kubernetes, and serverless architectures
• Design and implement robust MLOps strategies for lifecycle management

Integration & Compliance

• Ensure compliance with healthcare standards such as HIPAA, HL7, and FHIR
• Integrate AI systems with EHR/EMR platforms
• Implement ethical AI practices, regulatory compliance, and bias mitigation techniques

Collaboration & Leadership

• Work closely with business analysts, healthcare professionals, software engineers, and ML engineers
• Implement LangChain, OpenAI APIs, vector databases (Pinecone, FAISS, Weaviate), and RAG architectures
• Mentor and lead junior data scientists and engineers
• Contribute to AI research, publications, patents, and long-term AI strategy

Required Skills & Competencies

• Expertise in Machine Learning, Deep Learning, and Generative AI
• Strong Python programming skills
• Hands-on experience with PyTorch and TensorFlow
• Experience fine-tuning transformer-based LLMs (GPT, BERT, T5, LLaMA, etc.)
• Familiarity with ASR models (Whisper, Canary, wav2vec, DeepSpeech)
• Experience with text embeddings and vector databases
• Proficiency in cloud platforms (AWS, Azure, GCP)
• Experience with LangChain, OpenAI APIs, and RAG architectures
• Knowledge of agentic AI frameworks and reinforcement learning
• Familiarity with Docker, Kubernetes, and MLOps best practices
• Understanding of FHIR, HL7, HIPAA, and healthcare system integrations
• Strong communication, collaboration, and mentoring skills

Job Details

- Job Title: SDE-3

- Industry: Technology

- Domain - Information technology (IT)

- Experience Required: 5-8 years

- Employment Type: Full Time

- Job Location: Bengaluru

- CTC Range: Best in Industry

Role & Responsibilities

As a Software Development Engineer - 3, Backend Engineer at company, you will play a critical role in architecting, designing, and delivering robust backend systems that power our platform. You will lead by example, driving technical excellence and mentoring peers while solving complex engineering problems. This position offers the opportunity to work with a highly motivated team in a fast-paced and innovative environment.

Key Responsibilities:

Technical Leadership-

• Design and develop highly scalable, fault-tolerant, and maintainable backend systems using Java and related frameworks.
• Provide technical guidance and mentorship to junior developers, fostering a culture of learning and growth.
• Review code and ensure adherence to best practices, coding standards, and security guidelines.

System Architecture and Design-

• Collaborate with cross-functional teams, including product managers and frontend engineers, to translate business requirements into efficient technical solutions.
• Own the architecture of core modules and contribute to overall platform scalability and reliability.
• Advocate for and implement microservices architecture, ensuring modularity and reusability.

Problem Solving and Optimization-

• Analyze and resolve complex system issues, ensuring high availability and performance of the platform.
• Optimize database queries and design scalable data storage solutions.
• Implement robust logging, monitoring, and alerting systems to proactively identify and mitigate issues.

Innovation and Continuous Improvement-

• Stay updated on emerging backend technologies and incorporate relevant advancements into our systems.
• Identify and drive initiatives to improve codebase quality, deployment processes, and team productivity.
• Contribute to an advocate for a DevOps culture, supporting CI/CD pipelines and automated testing.

Collaboration and Communication-

• Act as a liaison between the backend team and other technical and non-technical teams, ensuring smooth communication and alignment.
• Document system designs, APIs, and workflows to maintain clarity and knowledge transfer across the team.

Ideal Candidate

• Strong Java Backend Engineer.
• Must have 5+ years of backend development with strong focus on Java (Spring / Spring Boot)
• Must have been SDE-2 for at least 2.5 years
• Hands-on experience with RESTful APIs and microservices architecture
• Strong understanding of distributed systems, multithreading, and async programming
• Experience with relational and NoSQL databases
• Exposure to Kafka/RabbitMQ and Redis/Memcached
• Experience with AWS / GCP / Azure, Docker, and Kubernetes
• Familiar with CI/CD pipelines and modern DevOps practices
• Product companies (B2B SAAS preferred)
• have stayed for at least 2 years with each of the previous companies
• (Education): B.Tech in computer science from Tier 1, Tier 2 colleges