50+ ETL Jobs in India

Job Title : Alteryx Developer

Experience : 5+ Years (Senior profiles with 8 to 12+ years preferred)

Location : Remote

Employment Type : Contract

Job Summary :

We are looking for an experienced Alteryx Developer to design, develop, and optimize enterprise ETL workflows, data transformation processes, and workflow automation solutions. The ideal candidate should have strong expertise in Alteryx Designer, Alteryx Server, SQL, ETL development, and enterprise data integration.

Mandatory Skills :

Alteryx Designer, Alteryx Server, ETL Development, Workflow Automation, SQL, Data Transformation, Data Migration, SQL Server/Oracle/MySQL/PostgreSQL, API Integration, Azure/AWS, Git.

Key Responsibilities :

• Design and develop scalable Alteryx workflows and ETL pipelines.
• Build reusable macros, analytic apps, and automated workflows.
• Perform data extraction, transformation, validation, and migration.
• Integrate data from databases, APIs, cloud platforms, and flat files.
• Manage Alteryx Server, workflow scheduling, deployment, and production support.
• Optimize workflow performance and ensure data quality.
• Collaborate with business and analytics teams to deliver data solutions.

Required Skills :

• Hands-on experience with Alteryx Designer and Alteryx Server.
• Strong expertise in ETL development, workflow automation, and data transformation.
• Proficiency in SQL with experience working on large datasets.
• Experience with SQL Server, Oracle, MySQL, or PostgreSQL.
• Knowledge of data migration, data validation, and data cleansing.
• Experience integrating data through APIs, cloud platforms, and flat files.
• Hands-on experience with Git and version control.
• Exposure to Azure or AWS cloud platforms.
• Strong analytical, troubleshooting, and performance optimization skills.

Good to Have :

• Python or Java
• Power BI, Tableau, or Spotfire
• Data Warehousing & Data Modeling
• CI/CD, Agile/Scrum
• Alteryx Designer Core Certification

Please find below the job description for Senior Azure Fabric Data Architect role with Wissen Technology.

Website and Company profile:

www.wissen.com

LinkedIn Page:

https://www.linkedin.com/company/wissen-technology/

Job Description:

Experience: 8–15+ Years

Location: Wissen Office (Pune/Bengaluru)

Position: 1

Job Summary

We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.

Key Responsibilities

• Design end-to-end data architecture using Microsoft Fabric.
• Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
• Define data ingestion, ETL/ELT, governance, security, and performance strategies.
• Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
• Work with business stakeholders to translate requirements into technical solutions.
• Mentor engineering teams and provide technical leadership.

Required Skills

• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
• Azure Data Engineering
• Power BI
• Azure AI Services / Azure OpenAI
• Data Architecture & Data Modeling
• SQL, Python
• Azure DevOps, CI/CD
• Strong stakeholder management and solution design experience

About the Role

We are looking for an experienced Snowflake Architect with 10+ years of overall IT experience and strong expertise in designing, implementing, and optimizing enterprise-scale data platforms using Snowflake. The ideal candidate will have a deep understanding of cloud data warehousing, data architecture, ETL/ELT frameworks, and data engineering best practices. This role requires close collaboration with business stakeholders, data engineers, architects, and analytics teams to build scalable, secure, and high-performing data solutions.

Key Responsibilities

·      Design and implement scalable, secure, and high-performance data architectures using Snowflake.

·      Define enterprise data models, data warehouse architecture, and best practices for data governance.

·      Design and optimize ELT/ETL pipelines for structured and semi-structured data.

·      Lead Snowflake implementation, migration, and modernization initiatives.

·      Optimize Snowflake performance, query execution, clustering, partitioning, and cost management.

·      Design data integration solutions using cloud-native and third-party ETL tools.

·      Establish security frameworks, role-based access control (RBAC), data masking, and governance policies. 

·      Collaborate with Data Engineers, BI Developers, Data Scientists, and business stakeholders to deliver end-to-end data solutions.

·      Conduct architecture reviews, performance tuning, and capacity planning.

·      Mentor technical teams and establish development standards and best practices.

·      Support CI/CD implementation and DevOps practices for data platforms.

·      Prepare technical documentation, architecture diagrams, and solution design documents. 

Required Skills & Experience

·      10+ years of overall IT experience with at least 5+ years of hands-on experience in Snowflake architecture and implementation.

·      Strong expertise in Snowflake Data Cloud architecture and administration.

·      Experience designing enterprise-scale data warehouse and lakehouse solutions.

·      Strong SQL programming and query optimization skills.

·      Experience with ETL/ELT tools such as Matillion, dbt, Informatica, Talend, Fivetran, or Azure Data Factory.

·      Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).

·      Hands-on experience with data modeling techniques (Star Schema, Snowflake Schema, Data Vault, Dimensional Modeling).

·      Experience with performance tuning, workload optimization, and Snowflake cost optimization.

·      Knowledge of data security, governance, encryption, and compliance best practices.

·      Experience with Git, CI/CD pipelines, and Agile development methodologies. 

Preferred Skills

·      Snowflake certifications (SnowPro Core or SnowPro Advanced).

·      Experience with Python, Scala, or Java for data engineering tasks. 

·      Knowledge of Apache Spark, Kafka, or other big data technologies.

·      Exposure to Power BI, Tableau, or other BI and visualization tools.

·      Experience working with large-scale enterprise data migration projects.

·      Understanding of DataOps and MLOps practices. 

Educational Qualification

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

Key Competencies

·      Strong analytical and problem-solving skills.

·      Excellent communication and stakeholder management abilities.

·      Proven experience in leading architecture discussions and technical solution design.

·      Ability to mentor teams and drive technical excellence.

·      Self-driven, proactive, and capable of working effectively in a remote environment.

About the Role

We are looking for a skilled SQL Server DBA with 4–5 years of experience in SQL Server database administration, performance tuning, and enterprise data integration. The ideal candidate should have hands-on experience working with Product Lifecycle Management (PLM) systems, ERP integrations, and data bridge solutions to enable seamless data exchange between enterprise applications.

Key Responsibilities

· Administer, monitor, and maintain Microsoft SQL Server databases to ensure high availability, security, and performance.

· Design, implement, and support PLM–ERP data bridge solutions for seamless integration between Product Lifecycle Management and ERP systems.

· Develop and optimize SQL queries, stored procedures, views, triggers, and database objects.

· Monitor database performance and perform query optimization, indexing, and troubleshooting.

· Design and implement database backup, recovery, disaster recovery, and high availability strategies.

· Build and maintain ETL processes and data synchronization workflows between PLM, ERP, and other enterprise applications. 

· Collaborate with application development teams to support database design and application deployments.

· Perform database migrations, upgrades, patching, and environment maintenance.

· Ensure database security, user management, and compliance with organizational standards.

· Create and maintain technical documentation, database architecture, and operational procedures. 

Required Skills & Experience

· 4–5 years of hands-on experience as a SQL Server DBA.

· Strong expertise in Microsoft SQL Server (2016/2019/2022 or later).

· Excellent knowledge of SQL, T-SQL, Stored Procedures, Functions, Triggers, Views, and Performance Tuning.

· Experience in database backup, restore, replication, indexing, and high availability (Always On, Log Shipping, Replication).

· Hands-on experience working with Product Lifecycle Management (PLM) systems.

· Experience implementing or supporting PLM–ERP data bridge/integration solutions.

· Knowledge of ERP systems such as SAP, Oracle E-Business Suite, Microsoft Dynamics, Infor, or similar platforms.

· Experience with ETL tools and enterprise data integration.

· Strong troubleshooting and root cause analysis skills. 

Preferred Skills

· Experience with Teamcenter, Windchill, Enovia, Arena PLM, or similar PLM platforms.

· Knowledge of SSIS, SSRS, and SSAS.

· Experience with PowerShell or Python scripting for database automation.

· Exposure to Azure SQL Database or cloud-based SQL environments. 

· Understanding of manufacturing, engineering, or product development processes.

· Familiarity with CI/CD and DevOps practices. 

Educational Qualification

· Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.

Key Competencies

· Strong analytical and problem-solving skills.

· Excellent communication and stakeholder management abilities.

· Ability to work independently in a remote environment.

· Strong attention to detail and commitment to database reliability and performance.

· Ability to manage multiple priorities in a fast-paced environment.

About Ritually

Ritually is building the definitive process discovery platform for back office work. Our product fuses underutilized system telemetry with computer vision to help large enterprise and scaling mid-market companies deeply understand and reimagine their highest value and most repetitive processes for a world where humans and agents work together. We're based in New York and Denver.

We believe deeply in trust (of our customers and each other), craft, customer obsession, and speed.

You'll be joining an AI-native, fast-moving, and repeat founding team. Ritually's founders previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.

The Role

This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0-1 You'll be tackling our largest technical challenges across technologies.

What You'll Do

• Design and build data pipelines that capture and turn high volumes of system activity into structured, queryable data.
• Turn raw activity streams into processes: sessionize event logs, cluster recurring sequences, and use LLMs to label and summarize what's happening.
• Build the evaluation backbone from scratch: stand up synthetic data generation pipelines that produce labeled scenarios to measure accuracy and catch regressions.
• Own data quality and privacy.
• Partner closely with the founders and the rest of engineering to ship features end to end.

What We're Looking For

• 1-4 years of experience in data engineering, AI/ML engineering, or backend work with a data focus (some of this can be project or research experience).
• Strong in Python and/or TypeScript, comfortable in SQL, and able to build data pipelines you can trust.
• Hands-on experience working with LLMs structured output, prompting, and wrangling non-determinism while keeping behavior reliable.
• A practical sense for evaluation: you know that "it looks right" isn't the same as "it's measurably right."
• Care about data privacy and handling sensitive information responsibly.
• Comfort with ambiguity and a real appetite to own a hard, open-ended problem.

Nice to Have

• Background in process mining, sequence / event-log analysis, or workflow analytics.
• Deeper PostgreSQL: window functions, partitioning, pg_cron, query performance.
• Embeddings and vector search (pgvector) or semantic retrieval.
• Familiarity with cloud infrastructure.
• Any prior early-stage startup experience.
• Degree in computer science or a related field.

Required Qualifications

• Bachelor’s degree in marketing, Business Analytics, Computer Science, Engineering, Statistics, Information Systems, or a related field.
• 5+ years of experience in marketing analytics, business intelligence, data analysis, or marketing operations.
• 3+ years of hands-on experience supporting B2B marketing organizations with reporting, campaign measurement, and analytics.
• Demonstrated experience owning enterprise marketing reporting ecosystems and KPI governance frameworks.
• Deep expertise in marketing attribution methodologies, email deliverability concepts, campaign tracking, and marketing performance measurement.
• Hands-on experience with marketing automation platforms, including Eloqua, is required.
• Advanced proficiency in SQL and experience working with large, complex datasets.
• Strong programming and data manipulation skills using Python.
• Hands-on experience with multiple BI and visualization platforms, including:
• Domo
• Snowflake
• Power BI
• Tableau
• Proven experience leading or supporting BI platform migrations and change management initiatives.
• Experience building and maintaining data models, ETL processes, and self-service analytics environments.
• Strong understanding of marketing data architecture, data governance, and metadata management.
• Excellent problem-solving skills with a strong attention to detail and commitment to data accuracy.
• Exceptional communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
• Ability to work independently, prioritize effectively, and manage multiple projects in a fast-paced environment.

Must-Have Qualifications

• 5+ years of experience in marketing analytics, business intelligence, or marketing operations.
• Proven ownership of marketing reporting infrastructure, KPI governance, and executive-level dashboards.
• Strong expertise in email marketing analytics, including deliverability, attribution, campaign tracking, and performance measurement.
• Hands-on experience with Eloqua and marketing automation ecosystems.
• Advanced SQL and Python skills for data extraction, transformation, analysis, and automation.
• Expert-level proficiency with Snowflake and at least two enterprise BI platforms, including Domo, Power BI, and Tableau.
• Demonstrated success leading BI platform migrations and reporting modernization initiatives.
• Experience partnering with marketing, marketing operations, IT, and data engineering teams.
• Strong understanding of data quality frameworks, governance, and reporting best practices.

Nice-to-Have Qualifications

• Experience with Salesforce CRM, Salesforce Marketing Cloud, HubSpot, Marketo, or similar platforms.
• Experience with modern data stack technologies, including dbt, Alteryx, or data orchestration tools.
• Knowledge of account-based marketing (ABM) measurement and customer journey analytics.
• Experience implementing self-service analytics programs.
• Familiarity with Agile methodologies and project management frameworks.
• Experience working within a global B2B technology organization.

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.

Data Engineer – Databricks & AWS (7+ Years)

Location: Baner, Pune

Work Model:5 days from office

Required Skills

• 7+ years of experience in Data Engineering with strong expertise in Databricks, PySpark, Apache Spark, and SQL.
• Hands-on experience building scalable ETL/ELT pipelines and Data Lake/Lakehouse solutions using Delta Lake.
• Experience with AWS services including S3, Glue, Lambda, IAM, EMR, and Redshift.
• Strong knowledge of Apache Airflow, Git, CI/CD, data quality, performance tuning, and production support.
• Experience with Kafka/Spark Streaming and Banking, Financial Services, or Credit Bureau domains is preferred.

Roles & Responsibilities

• Designed and developed scalable data pipelines using Databricks, PySpark, and AWS to process large-scale credit bureau, customer, loan, and repayment datasets.
• Built ETL/ELT workflows and Delta Lake-based data models to support credit risk analytics, regulatory reporting, and customer profiling.
• Developed and orchestrated batch and near real-time data processing pipelines using Airflow, Kafka, and Spark, ensuring data quality and reliability.
• Optimized Spark workloads through performance tuning techniques, improving processing efficiency and reducing execution time.
• Collaborated with business stakeholders, data architects, and risk teams to deliver data solutions while supporting production environments and operational excellence.

NOTE: One technical round is mandatory to be taken F2F from Pune office.

CAW We are looking for a Application Support Engineer to lead customer onboarding, deployments, and production support on the platform. This role sits at the intersection of engineering, customer success, and product and requires strong technical depth combined with excellent skills. You will work directly with enterprise customers to ensure fast, reliable deployments and long-term technical success. This is not a traditional support role; it's a high-ownership, hands-on techno-support and deployment engineering role.

The candidate will have responsibilities across the following functions:

Customer Deployment and Onboarding:

● Own end-to-end deployment of our platform for enterprise customers. ● Configure integrations, workflows, and environment-specific setups.

● Drive fast go-live and post-deployment stabilization.

Customer Interaction and Requirement Gathering:

● Act as the primary technical point of contact for customers.

● Understand customer business flows, data needs, and system constraints.

● Translate requirements into clear technical inputs for Product and Engineering teams.

Production Support (L1 and L2):

● Handle L1/L2 production support for customer-reported issues.

● Debug data, integration, performance, and infrastructure issues.

● Act as a technical escalation point during critical incidents.

Data and ETL Support:

● Understand and troubleshoot ETL pipelines and data workflows.

● Support ingestion, transformation, validation, and reconciliation of data.

● Work with APIs, databases, and file-based integrations.

Product Feedback and Documentation:

● Share real-world customer feedback, gaps, and edge cases with Product teams.

● Create deployment guides, runbooks, and internal documentation.

Requirements:

● 4-8 years of experience in customer-facing technical roles.

● Strong understanding of ETL pipelines and data workflows.

● Experience working with AWS, GCP, or Azure cloud environments.

● Knowledge of cloud networking fundamentals.

● Knowledge of Java, Spring Boot, Python, and Postgres is a must.

● Familiarity with SQL, APIs, monitoring, and logging tools.

● Strong troubleshooting and problem-solving skills.

● Excellent written and verbal communication skills.

● Experience with SaaS, FinTech, or enterprise platforms.

● Prior roles in Solutions Engineering, Deployment Engineering, or Technical Support (L2/L3).

● Startup or high-growth environment experience.

● Effective Communication: Clear and precise communication to collaborate effectively across teams.

● Curiosity and Growth: A proactive learner with a passion for continuous improvement and innovation.

About CAW Studios

CAW Studios is a Product Engineering Company of 150+ geeks.

We have built these products - Interakt, CashFlo, KaiPulse, and FastBar. And we still run their complete engineering.

We are part of the engineering teams for Haptik, EmailAnalytics, GrowthZone, Reliance General Insurance, and KWE Logistics.

We are obsessed with automation, DevOps, OOPS, and SOLID. We are not into one tech-stack - we are into solving problems.

Find us: https://goo.gl/maps/dvR6L26JUa42

Website: https://www.caw.tech/

Job Title : Report (Power BI) Engineer / Developer

Experience : 5+ Years

Work Mode : Remote (4 days/month office visit)

Locations : Noida, Hyderabad, Chennai, Pune, Bengaluru

Job Summary :

We are looking for an experienced Report (Power BI) Engineer / Developer to design and develop business-critical reporting solutions. The ideal candidate should have strong expertise in Power BI dashboards and paginated reports, along with hands-on experience in SQL Server, Snowflake, and Databricks.

Mandatory Skills :

Power BI, Power BI Dashboards, Paginated Reports, SQL Server, T-SQL, Snowflake, Databricks, Data Warehousing, ETL, SQL Query Optimization.

Key Skills Required :

• 5+ years of experience in Power BI development.
• Strong hands-on experience with Power BI Dashboards and Paginated Reports.
• Excellent knowledge of SQL Server and T-SQL development.
• Experience with Snowflake and Databricks.
• Understanding of data warehousing concepts, ETL processes, and SQL performance optimization.
• Strong communication and collaboration skills.

Preferred Skills :

• Experience with cloud data modernization projects.
• Knowledge of data security and compliance practices.

Note : Comprehensive background verification, including education, employment, criminal, credit, and drug screening, is mandatory.

Key Skills:

Technical Skills

• Power BI Development: 4-5 years of hands-on experience developing Power BI reports, dashboards, and data models
• DAX: Strong proficiency in DAX (Data Analysis Expressions) for creating measures, calculated columns, and complex calculations
• Power Query / M Language: Expertise in data transformation and ETL processes using Power Query
• Data Modeling: Solid understanding of dimensional modeling, star schema, and data warehouse concepts
• SQL: Proficient in SQL for data extraction, manipulation, and querying relational databases
• Power BI Service: Experience with Power BI Service administration, workspace management, scheduled refreshes, and deployment pipelines
• Custom Visualizations: Experience creating and configuring custom visuals, including use of AppSource visuals and custom visual development using Power BI Visuals SDK
• API Integration: Hands-on experience with Power BI REST APIs for automating deployments, managing workspaces, and embedding reports
• Knowledge of data visualization best practices and UI/UX principles for dashboard design
• Experience with data source connectivity (SQL Server, Azure SQL, Oracle, SAP, Excel, APIs, web services)

Additional Required Qualifications

• Bachelor’s degree in computer science, Information Systems, Business Analytics, or related field
• Strong analytical and problem-solving abilities
• Excellent communication skills to work with both technical and non-technical stakeholders
• Ability to manage multiple projects and prioritize tasks effectively
• Detail-oriented with commitment to delivering high-quality work
• Client-facing experience with ability to gather requirements and present solutions

Preferred Qualifications

• Microsoft Power BI certification (PL-300 or equivalent)
• Experience with Azure ecosystem (Azure Data Factory, Azure Synapse Analytics, Azure SQL Database)
• Knowledge of other Microsoft BI tools (SSRS, SSAS, Excel Power Pivot)
• Familiarity with Python or R for advanced analytics integration
• Experience with Dataflows and incremental refresh strategies
• Understanding of API development for custom visuals or Power BI embedded solutions
• Experience working in Agile/Scrum development environments

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build and optimize data architectures, data lakes, and warehousing solutions.
• Integrate data from multiple APIs, databases, and third-party systems.
• Ensure data quality, consistency, security, and reliability across systems.
• Develop automated workflows for data ingestion, transformation, and validation.
• Work with structured and unstructured datasets at scale.
• Optimize SQL queries and database performance.
• Collaborate with backend, analytics, and AI teams for data-driven solutions.
• Monitor pipelines and troubleshoot production issues.
• Implement logging, monitoring, and alerting mechanisms for data systems.
• Maintain proper technical documentation and workflow diagrams.

Required Skills & Qualifications

• 2+ years of experience as a Data Engineer or similar role.
• Strong proficiency in SQL and database design.
• Experience with relational and NoSQL databases such as:
• MySQL
• PostgreSQL
• MongoDB
• BigQuery / Redshift / Snowflake
• Hands-on experience with ETL tools and data pipeline development.
• Strong programming skills in at least one language:
• Python
• Node.js
• Java
• Experience with cloud platforms:
• AWS / GCP / Azure
• Familiarity with data orchestration tools:
• Airflow
• Prefect
• Dagster
• Understanding of APIs, webhooks, and real-time data processing.
• Experience with Git and CI/CD workflows.
• Knowledge of Docker and containerized deployments.
• Good understanding of data security and governance practices.

Preferred Qualifications

• Experience with Apache Spark, Kafka, or distributed processing systems.
• Exposure to AI/ML data pipelines.
• Knowledge of analytics and BI tools such as:
• Power BI
• Tableau
• Looker
• Experience working in startup or fast-paced product environments.
• Familiarity with microservices architecture.

What We Offer

• Opportunity to work on scalable and impactful data systems.
• Collaborative and growth-focused work environment.
• Exposure to AI, analytics, and cloud-native technologies.
• Flexible work culture and learning opportunities.
• Competitive salary and performance-based growth.

Role Overview

We are seeking a Senior SQL Developer & ETL Engineer with 5+ years of experience for a 100% remote opportunity.

Please Note: This is not a pure Data Engineering role. We are looking for a true SQL Specialist. Your core strength must lie in relational database development, schema design, and writing high-performance database logic with Python, ETL, Cloud. SQL mastery and database architecture are the absolute heart of this role.

If you are a database developer who loves diving into query execution plans, refactoring messy stored procedures for 10x performance, and building clean data models from scratch, this role is for you.

Key Responsibilities

1. Database Architecture & Schema Design

• Design, implement, and maintain robust relational database schemas.
• Architect optimal data models for both operational (OLTP) and analytical (OLAP/Data Warehousing) workloads.
• Implement Normalization (3NF) and dimensional modeling (Star/Snowflake schemas) as required.

2. Advanced Database Programmability

• Write, debug, and optimize highly complex Stored Procedures, Functions, Triggers, and Views to handle core business logic at the database level.
• Utilize advanced SQL techniques such as CTEs, Window Functions, and complex analytical queries to solve business problems.

3. Performance Tuning & Indexing

• Analyze query execution plans, identify performance bottlenecks, and implement advanced indexing strategies (B-Tree, Clustered/Non-Clustered, Partitioning).
• Refactor legacy SQL code and manage statistics, locking, and concurrency mechanisms to ensure sub-second response times.

4. Python & Cloud ETL/ELT Pipelines

• Develop, schedule, and maintain scalable data ingestion and transformation pipelines to connect disparate data sources.
• Leverage Cloud Data Platforms alongside modern Python libraries to build efficient data movement workflows.

5. Data Integrity & Governance

• Establish strict database constraints, data validation routines, and automated quality checks to guarantee absolute data accuracy.

Required Technical Skills

• Expert-Level SQL & DB Programmability (5+ Years): Mastery of writing server-side logic (Stored Procedures/Functions) and complex queries in enterprise platforms like PostgreSQL, SQL Server, Oracle, or MySQL.
• Advanced Database Optimization: Deep, under-the-hood understanding of database engines, execution plans, indexing strategies, and concurrency/locking control.
• Python for Data Engineering (3+ Years): Proficient in writing clean, modular Python scripts for API integration, data manipulation, and ETL processing (using libraries like Pandas, SQLAlchemy, or custom database connectors).
• Cloud Data Experience: Hands-on experience working with, migrating to, or developing within major cloud environments (AWS, Azure, GCP) and modern cloud data warehouses (Snowflake, BigQuery, or Redshift).
• Data Modeling Methodologies: Practical experience designing Star/Snowflake schemas, handling Slowly Changing Dimensions (SCD), and balancing normalization vs. denormalization.

Remote & Soft Skills

• Legacy Refactoring Mindset: You genuinely enjoy opening up a massive, poorly optimized 500-line legacy stored procedure and refactoring it for maximum efficiency.
• Autonomous Execution: Proven ability to manage your own time, architecture tasks, and deliverables without micromanagement in a fully remote setup.
• Asynchronous Communication: Exceptional written and verbal English communication skills to collaborate seamlessly across time zones.

Nice-to-Haves

• Experience migrating legacy on-premise infrastructure and stored procedures to modern cloud data warehouses.
• Familiarity with workflow orchestration tools like Apache Airflow or Prefect.
• Hands-on experience with dbt (data build tool) for in-warehouse transformations.

About the Role:

We are looking for a highly skilled Data Engineer with a strong foundation in Power BI, SQL, Python, and Big Data ecosystems to help design, build, and optimize end-to-end data solutions. The ideal candidate is passionate about solving complex data problems, transforming raw data into actionable insights, and contributing to data-driven decision-making across the organization.

Key Responsibilities:

• Data Modelling & Visualization
• Build scalable and high-quality data models in Power BI using best practices.
• Define relationships, hierarchies, and measures to support effective storytelling.
• Ensure dashboards meet standards in accuracy, visualization principles, and timelines.
• Data Transformation & ETL
• Perform advanced data transformation using Power Query (M Language) beyond UI-based steps.
• Design and optimize ETL pipelines using SQL, Python, and Big Data tools.
• Manage and process large-scale datasets from various sources and formats.
• Business Problem Translation
• Collaborate with cross-functional teams to translate complex business problems into scalable, data-centric solutions.
• Decompose business questions into testable hypotheses and identify relevant datasets for validation.
• Performance & Troubleshooting
• Continuously optimize performance of dashboards and pipelines for latency, reliability, and scalability.
• Troubleshoot and resolve issues related to data access, quality, security, and latency, adhering to SLAs.
• Analytical Storytelling
• Apply analytical thinking to design insightful dashboards—prioritizing clarity and usability over aesthetics.
• Develop data narratives that drive business impact.
• Solution Design
• Deliver wireframes, POCs, and final solutions aligned with business requirements and technical feasibility.

Required Skills & Experience:

• Minimum 3+ years of experience as a Data Engineer or in a similar data-focused role.
• Strong expertise in Power BI: data modeling, DAX, Power Query (M Language), and visualization best practices.
• Hands-on with Python and SQL for data analysis, automation, and backend data transformation.
• Deep understanding of data storytelling, visual best practices, and dashboard performance tuning.
• Familiarity with DAX Studio and Tabular Editor.
• Experience in handling high-volume data in production environment.
• Exposure to Big Data technologies such as:
• PySpark (must have)
• Hadoop
• Hive / HDFS
• Spark Streaming (optional but preferred)

Why Join Us?

• Work with a team that's passionate about data innovation.
• Exposure to modern data stack and tools.
• Flat structure and collaborative culture.
• Opportunity to influence data strategy and architecture decisions.

About Marseer AI

Marseer AI (www.marseerai.com) is a modular AI activation platform built for DTC and retail e-commerce brands. damStack is Marseer AI's Snowflake-native, dbt-driven data and marketing activation product. It follows a Listen -> Reflect -> React architecture across composable applications, each running inside a customer's own Snowflake data warehouse.

Role Overview

We are looking for a Senior Data Engineer to join the damStack engineering team at Marseer AI. You will design and implement data pipelines, dbt transformation models, and Snowflake-native data products for retail and e-commerce brands. This is a hands-on, high-ownership role across ingestion, transformation, activation workflows, and client onboarding.

What You Will Do

- Design, build, and maintain dbt models across staging, intermediate, and mart layers for customer identity, segmentation, journey orchestration, and activation outputs.

- Implement incremental dbt models, snapshots, and tests to ensure data freshness, accuracy, and reliability.

- Contribute to damStack's Open Schema and unified customer_360 semantic layer.

- Build and refine SQL-based rule engines in Snowflake for priority resolution, frequency capping, and activation orchestration.

- Configure and manage Airbyte connectors for bidirectional data sync such as MongoDB to Snowflake and Snowflake to Klaviyo.

- Build and maintain Dagster pipelines to orchestrate dbt runs, Airbyte sync jobs, and cross-pipeline dependencies.

- Support integration of external marketing platforms into the damStack data layer.

- Work directly with client brands to understand data sources, schemas, and business requirements.

- Translate client data into damStack's standardized activity schema and entity resolution framework.

- Troubleshoot data quality and integration issues in client environments.

- Contribute to single-tenant Snowflake deployments, data quality tests, monitors, alerting, and technical design documentation.

Requirements

- 5+ years of professional experience in data engineering.

- Advanced proficiency in dbt Core or Cloud, including incremental models, snapshots, tests, macros, and multi-layer DAG design.

- Strong hands-on Snowflake experience, including DDL/DML, Snowflake Tasks, query optimization, and multi-tenant data architecture.

- Expert-level SQL, including window functions, CTEs, complex joins, and performance tuning.

- Ability to communicate pipeline designs and technical decisions clearly to technical and non-technical stakeholders.

Strongly Preferred

- Experience with Airbyte or comparable ELT / connector platforms.

- Familiarity with Dagster or similar orchestration tools such as Airflow or Prefect.

- Prior experience in a SaaS or data product company shipping reusable, multi-tenant data infrastructure.

- Understanding of identity resolution patterns, surrogate key architectures, customer data platforms, or experimentation / A/B testing data pipelines.

Good to Have

- Familiarity with Klaviyo or other marketing activation / ESP platforms.

- Experience with MongoDB or document-store integrations.

- Prior experience in retail or e-commerce data domains.

What We Are Looking For

- Availability for US business hours, with at least 5 hours of overlap with America/New_York.

- Ownership mindset, attention to schema naming, test coverage, documentation, and reliable pipelines.

- Collaborative, structured communication with a distributed team.

What We Offer

- Compensation range: INR 20-30 LPA.

- Fully remote role; work from anywhere in India, with Hyderabad-based candidates preferred.

- High-ownership engineering work on Snowflake, dbt, Airbyte, and Dagster.

- Direct exposure to real DTC and retail e-commerce data problems at scale.

- A small, senior team where your contributions are visible.

Job Title : Analytics Engineer

Experience : 6+ Years

Location : Gurgaon | Bangalore | Ahmedabad | Chennai

Work Mode : Work From Office

Employment Type : Contract (6 Months)

About the Role :

We are looking for an experienced Analytics Engineer to design, develop, and optimize scalable data models and analytics solutions that drive business decision-making. The ideal candidate should have strong expertise in SQL, dbt, data modeling, data quality, and modern analytics engineering practices.

Mandatory Skills :

SQL, dbt, Data Modeling, Data Warehousing, ETL/ELT, Query Optimization, Data Quality, Git, CI/CD, Analytics Engineering, Data Transformation, Data Governance, Stakeholder Management.

Key Responsibilities :

• Design and maintain scalable data warehouse models, data marts, and analytical datasets.
• Build and optimize data transformation pipelines using SQL and dbt.
• Develop high-performance SQL queries using CTEs, Window Functions, Complex Joins, and Analytical Functions.
• Implement data quality checks, testing frameworks, and governance best practices.
• Manage end-to-end analytics development lifecycle, from requirement gathering to deployment.
• Work with Git, CI/CD pipelines, and version control best practices.
• Collaborate with business and technical stakeholders to deliver reliable analytics solutions.
• Troubleshoot and optimize data pipelines, models, and query performance.

Required Skills :

• 6+ years of experience in Analytics Engineering, Data Engineering, or related roles.
• Strong expertise in SQL and query performance optimization.
• Hands-on experience with dbt (Data Build Tool).
• Strong understanding of data modeling and data warehousing concepts.
• Experience with Git, CI/CD, and software development best practices.
• Knowledge of data quality frameworks, testing, and validation techniques.
• Ability to independently manage design, development, testing, documentation, and deployment.

Preferred Skills :

• Experience with cloud-based data platforms.
• Exposure to orchestration and scheduling tools.
• Understanding of data governance and compliance frameworks.
• Experience in performance tuning and cost optimization.
• Prior mentoring or technical leadership experience.

What We're Looking For :

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in a fast-paced environment.
• Passion for building scalable, reliable, and high-quality analytics solutions.

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

Job description:

Role Overview

We are seeking a Senior SQL Developer & ETL Engineer with 5+ years of experience for a 100% remote opportunity.

Please note: This is not a standard Big Data / Infra-heavy Data Engineering role. We are specifically looking for a SQL Specialist. Your core strength must lie in relational database development, schema design, and writing high-performance database logic. Python will be your primary tool for moving and orchestrating data, but SQL and database architecture are the heart of this role.

Key Responsibilities

• Database Architecture & Schema Design: Design, implement, and maintain robust relational database schemas, ensuring optimal data modeling (OLTP and OLAP/Data Warehousing).
• Advanced Database Programmability: Write, debug, and optimize complex Stored Procedures, Functions, Triggers, and Views to handle core business logic at the database level.
• Performance Tuning & Indexing: Analyze query execution plans, identify bottlenecks, and implement advanced indexing strategies, partitioning, and query refactoring to ensure sub-second response times.
• Python ETL/ELT Pipelines: Develop, schedule, and maintain scalable data ingestion and transformation pipelines using Python to connect disparate data sources.
• Data Integrity & Governance: Establish constraints, data validation routines, and automated quality checks to guarantee absolute data accuracy.

Required Technical Skills

• Expert-Level SQL & DB Programmability (5+ Years): Mastery of writing complex queries (CTEs, Window Functions, Analytical queries) and server-side logic (Stored Procedures/Functions) in platforms like PostgreSQL, SQL Server, Oracle, or MySQL.
• Advanced Database Optimization: Deep understanding of how databases work under the hood—specifically indexing (B-Tree, Hash, Clustered/Non-Clustered), execution plans, statistics, and locking/concurrency mechanisms.
• Python for Data Ingestion (3+ Years): Proficient in writing clean, modular Python scripts for data manipulation, API integration, and ETL processing (using libraries like Pandas, SQLAlchemy, or custom database connectors).
• Data Modeling Methodologies: Practical experience designing Star/Snowflake schemas, Normalization (3NF), and handling Slowly Changing Dimensions (SCD).

Remote & Soft Skills

• Autonomous Execution: Proven ability to manage your own time, architecture tasks, and deliverables without micromanagement.
• Asynchronous Communication: Exceptional written and verbal English communication skills to collaborate seamlessly across time zones.
• Legacy Refactoring Mindset: You enjoy opening up a massive, poorly optimized 500-line stored procedure and refactoring it for 10x performance.

Nice-to-Haves

• Experience migrating legacy on-premise stored procedures to modern cloud data warehouses (Snowflake, BigQuery, Redshift).
• Familiarity with workflow orchestration tools like Apache Airflow or Prefect.
• Experience with dbt (data build tool).

Work Location: Remote

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)

Role : AWS Data Engineer

Location : Anywhere in India - where cognizant office is available 

Contract duration : 12 months contract

Total Experience : 8-10 years

Budget-15LPA

Relevant Experience : 5+years with required skills & data engineering

Client : Cognizant

Job description : 

Python

Spark

Gradle 

AWS Services (ex: S3, Athena, Redshift, Transfer, SNS, SQS, Event Bridge, Lamda, Glue Data Catalog, RDS, EC2, IAM, Flink)

Kubernetes

Argo

Kafka / Kinesis streaming

SQL

ETL Data Pipelines

Data Modelling

Power BI/ Any reporting tools

New Relic / Terraform

Operational support - Batch monitoring, root cause analysis and fix

Job Title: Integration Engineer

Integration Engineers are responsible for defining, developing, delivering, maintaining and supporting end-to-end Enterprise Integration solutions. Using a designated IPaaS solution (e.g. Boomi), Integration Engineers integrate multiple cloud and on-premise applications which help customers publish and consume data between Oddr and third party systems for a variety of tasks.

Job Summary:

We are seeking a skilled and experienced Integration Engineer to join our Technology team in India. The ideal candidate will have a strong background in implementing low-code/no-code integration platforms as a service (iPaaS), with a preference for experience in Boomi. The role requires an in-depth understanding of SQL and RESTful APIs. Experience with Intapp's Integration Builder is a significant plus.

Key Responsibilities:

- Design and implement integration solutions using iPaaS tools.

- Collaborate with customers, product, engineering and business stakeholders to translate business requirements into robust and scalable integration processes.

- Develop and maintain SQL queries and scripts to facilitate data manipulation and integration.

- Utilize RESTful API design and consumption to ensure seamless data flow between various systems and applications.

- Lead the configuration, deployment, and ongoing management of integration projects.

- Troubleshoot and resolve technical issues related to integration solutions.

- Document integration processes and create user guides for internal and external users.

- Stay current with the latest developments in iPaaS technologies and best practices.

Qualifications:

- Bachelor’s degree in Computer Science, Information Technology, or a related field.

- Minimum of 2 years’ experience in an integration engineering role with hands-on experience in an iPaaS tool, preferably Boomi.

- Proficiency in SQL and experience with database management and data integration patterns.

- Strong understanding of integration patterns and solutions, API design, and cloud-based technologies.

- Good understanding of RESTful APIs and integration.

- Excellent problem-solving and analytical skills.

- Strong communication and interpersonal skills, with the ability to work effectively in a team environment.

- Experience with various integration protocols (REST, SOAP, FTP, etc.) and data formats (JSON, XML, etc.).

Preferred Skills:

- Boomi (or other iPaaS) certifications

- Experience with Intapp's Integration Builder is highly desirable but not mandatory.

- SQL Knowledge is important

- Experience in building E2E integrations and communicating with stakeholders

- Knowledge of Azure Functions, LogicApps, And other Azure Services is highly desirable

What we offer:

- Competitive salary and benefits package.

- Dynamic and innovative work environment.

- Opportunities for professional growth and advancement.

We are looking for an experienced Data Engineer with 4+ years of expertise in Python development, ETL processes, and Power BI reporting. The ideal candidate will be responsible for designing scalable data pipelines, optimizing data workflows, and delivering business intelligence solutions for data-driven decision-making.

Key Responsibilities

• Design, develop, and maintain robust ETL/data integration pipelines.
• Develop scalable data processing solutions using Python.
• Create and optimize complex SQL queries, stored procedures, and database solutions.
• Build interactive dashboards, reports, and data visualizations using Power BI.
• Integrate data from multiple sources including APIs, databases, and cloud platforms.
• Perform data cleansing, transformation, and validation to ensure data accuracy.
• Work closely with business and technical teams to gather reporting and analytics requirements.
• Monitor, troubleshoot, and improve data pipeline performance.
• Support data warehousing, reporting, and analytics initiatives.
• Mentor junior team members and contribute to best practices in data engineering.

Required Skills

• 4+ years of experience in Data Engineering or related roles.
• Strong hands-on experience in Python scripting and automation.
• Good experience with ETL processes and data pipeline development.
• Strong SQL skills with experience in relational databases.
• Hands-on experience in Power BI dashboard and report creation.
• Knowledge of data modeling and data warehousing concepts.
• Experience with APIs and data integration techniques.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.

We are seeking a highly analytical and detail-oriented Senior Data Analyst to lead data management, reporting, automation, and system development initiatives across the organization. The role focuses on transforming raw data into meaningful insights, designing and implementing automated systems, strengthening data structures, and supporting cross-functional teams with accurate, actionable intelligence to drive strategic and operational business decisions.

Key Responsibilities

1. Data Management & Reporting

• Collect, clean, validate, and consolidate data from multiple internal and external sources.
• Prepare and deliver daily, weekly, and monthly MIS reports for management and departments.
• Design, develop, and maintain dashboards to track KPIs, performance metrics, and operational trends.

2. Database & Data Accuracy Management

• Manage and regularly update internal databases, spreadsheets, and reporting systems.
• Ensure data accuracy, consistency, integrity, and confidentiality across all platforms.
• Implement best practices for data validation, version control, and audit checks.

3. Data Analysis & Business Insights

• Analyze large and complex datasets to identify trends, patterns, gaps, and anomalies.
• Translate data findings into clear, actionable insights and recommendations to support strategic and operational decision-making.

4. Reporting Automation, System Recommendation & Implementation

• Identify opportunities to replace manual or semi-manual processes with automated, data-driven systems.
• Design and implement automated reporting frameworks, dashboards, and data pipelines using Excel (Power Query, VBA, Macros), SQL, BI tools, and Python.
• Proactively suggest new automation tools, system enhancements, or integrations to improve efficiency, accuracy, and scalability.
• Lead the end-to-end implementation of approved automation initiatives, including requirement gathering, system design, testing, deployment, and stabilization.
• Continuously monitor and optimize automated systems in line with business growth and evolving data needs.

5. Cross-Functional Coordination & Support

• Collaborate with Sales, HR, Finance, Operations, and other departments to understand reporting and data requirements.
• Provide support for ad-hoc analysis, custom reports, and special data requests.
• Act as a data partner to department heads for decision support and performance tracking.

6. Documentation & Compliance

• Maintain complete and updated documentation for MIS processes, reports, data models, automation logic, and system changes.
• Ensure compliance with company data governance policies and applicable data protection standards.

System Development & Data Structuring Responsibilities

• Study and understand departmental workflows to evaluate how data is generated, processed, and utilized.
• Review existing manual and digital data systems to identify operational gaps, risks, and improvement opportunities.
• Recommend structured data models, reporting formats, and storage solutions aligned with business requirements.
• Coordinate with department heads to define data structures, access levels, and reporting standards.
• Implement new or upgraded data systems (Excel-based models, cloud platforms, ERP integrations) with minimal operational disruption.
• Design structured data formats and role-based access controls to ensure secure and organized data management.
• Train employees on newly implemented systems and provide post-implementation support.
• Monitor system performance, resolve issues, and continuously improve systems based on user feedback and organizational growth.

Qualifications & Experience

• Bachelor’s degree in Commerce, Statistics, Computer Applications, or a related field.
• 3–5 years of experience in data analytics, reporting, or system automation roles.
• Strong analytical thinking, logical reasoning, and problem-solving abilities.
• High attention to detail with excellent organizational and documentation skills.

Technical Skills (Must Have)

• Advanced Excel: Power Query, Power Pivot, VBA basics, Macros, Charts
• Python or R: Data cleaning, analysis, automation (Pandas, NumPy, etc.)
• BI Tools: Power BI or Tableau (DAX, data modeling, dashboard optimization)
• Data Warehousing Concepts: ETL processes, OLAP, Star/Snowflake schema
• Google Apps Script: Automation in Google Sheets, custom functions, triggers, API integrations, workflow optimization

Data Engineer — AI / BI

Artificial Intelligence & Business Intelligence | Data & Analytics

Who We Are:

Since our inception back in 2006, Navitas has grown to be an industry leader in the digital transformation space, and we’ve served as trusted advisors supporting our client base within the commercial, federal, and state and local markets.

What We Do:

At our very core, we’re a group of problem solvers providing our award-winning technology solutions to drive digital acceleration for our customers! With proven solutions, award-winning technologies, and a team of expert problem solvers, Navitas has consistently empowered customers to use technology as a competitive advantage and deliver cutting-edge transformative solutions.

Position Overview

We are seeking a Databricks Engineer to design, build, and operate a Data & AI platform with a strong foundation in the Medallion Architecture (raw/bronze, curated/silver, and mart/gold layers). This platform will orchestrate complex data workflows and scalable ELT pipelines to integrate data from enterprise systems such as PeopleSoft, D2L, and Salesforce, delivering high-quality, governed data for machine learning, AI/BI, and analytics at scale.

You will play a critical role in engineering the infrastructure and workflows that enable seamless data flow across the enterprise, ensure operational excellence, and provide the backbone for strategic decision-making, predictive modeling, and innovation

Responsibilities:

Data & AI Platform Engineering (Databricks-Centric):

• Design, implement, and optimize end-to-end data pipelines on Databricks, following the Medallion Architecture principles.
• Build robust and scalable ETL/ELT pipelines using Apache Spark and Delta Lake to transform raw (bronze) data into trusted curated (silver) and analytics-ready (gold) data layers.
• Operationalize Databricks Workflows for orchestration, dependency management, and pipeline automation.
• Apply schema evolution and data versioning to support agile data development.

Platform Integration & Data Ingestion:

• Connect and ingest data from enterprise systems such as PeopleSoft, D2L, and Salesforce using APIs, JDBC, or other integration frameworks.
• Implement connectors and ingestion frameworks that accommodate structured, semi-structured, and unstructured data.
• Design standardized data ingestion processes with automated error handling, retries, and alerting.

 Data Quality, Monitoring, and Governance:

• Develop data quality checks, validation rules, and anomaly detection mechanisms to ensure data integrity across all layers.
• Integrate monitoring and observability tools (e.g., Databricks metrics, Grafana) to track ETL performance, latency, and failures.
• Implement Unity Catalog or equivalent tools for centralized metadata management, data lineage, and governance policy enforcement.

Security, Privacy, and Compliance:

• Enforce data security best practices including row-level security, encryption at rest/in transit, and fine-grained access control via Unity Catalog.
• Design and implement data masking, tokenization, and anonymization for compliance with privacy regulations (e.g., GDPR, FERPA).
• Work with security teams to audit and certify compliance controls.

   AI/ML-Ready Data Foundation:

• Enable data scientists by delivering high-quality, feature-rich data sets for model training and inference.
• Support AIOps/MLOps lifecycle workflows using MLflow for experiment tracking, model registry, and deployment within Databricks.
• Collaborate with AI/ML teams to create reusable feature stores and training pipelines.

Cloud Data Architecture and Storage:

• Architect and manage data lakes on Azure Data Lake Storage (ADLS) or Amazon S3, and design ingestion pipelines to feed the bronze layer.
• Build data marts and warehousing solutions using platforms like Databricks.
• Optimize data storage and access patterns for performance and cost-efficiency.

 Documentation & Enablement:

• Maintain technical documentation, architecture diagrams, data dictionaries, and runbooks for all pipelines and components.
• Provide training and enablement sessions to internal stakeholders on the Databricks platform, Medallion Architecture, and data governance practices.
• Conduct code reviews and promote reusable patterns and frameworks across teams.

  Reporting and Accountability:

• Submit a weekly schedule of hours worked and progress reports outlining completed tasks, upcoming plans, and blockers.
• Track deliverables against roadmap milestones and communicate risks or dependencies.

Required Qualifications:

• Hands-on experience with Databricks, Delta Lake, and Apache Spark for large-scale data engineering.
• Deep understanding of ELT pipeline development, orchestration, and monitoring in cloud-native environments.
• Experience implementing Medallion Architecture (Bronze/Silver/Gold) and working with data versioning and schema enforcement in enterprise grade environments.
• Strong proficiency in SQL, Python, or Scala for data transformations and workflow logic.
• Proven experience integrating enterprise platforms (e.g., PeopleSoft, Salesforce, D2L) into centralized data platforms.
• Familiarity with data governance, lineage tracking, and metadata management tools.

Preferred Qualifications:

• Prior UMGC or USM experience preferred.
• Experience with Databricks Unity Catalog for metadata management and access control.
• Experience deploying ML models at scale using MLFlow or similar MLOps tools.
• Familiarity with cloud platforms like Azure or AWS, including storage, security, and networking aspects.
• Knowledge of data warehouse design and star/snowflake schema modeling.

Equal Employer/Veterans/Disabled

Navitas Business Consulting is an affirmative action and equal opportunity employer. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Navitas Human Resources.

Navitas is an equal opportunity employer. We provide employment and opportunities for advancement, compensation, training, and growth according to individual merit, without regard to race, color, religion, sex (including pregnancy), national origin, sexual orientation, gender identity or expression, marital status, age, genetic information, disability, veteran-status veteran or military status, or any other characteristic protected under applicable Federal, state, or local law. Our goal is for each staff member to have the opportunity to grow to the limits of their abilities and to achieve personal and organizational objectives. We will support positive programs for equal treatment of all staff and full utilization of all qualified employees at all levels within Navitas.

About LJI

Loyalty Juggernaut (LJI) is a leading B2B SaaS company redefining how enterprises drive customer engagement and loyalty. Our flagship platform, GRAVTY®, enables global brands to transform loyalty programs into measurable, revenue-generating growth engines.

Built as an AI-first, next-generation solution, GRAVTY® empowers organizations to deliver highly personalized, real-time experiences at scale—helping them increase customer lifetime value and deepen brand relationships.

Headquartered in Palo Alto, California, LJI partners with leading enterprises across 16 major industries including airlines, retail, hospitality, financial services and telecommunications powering some of the most innovative loyalty ecosystems worldwide.

Our Global Impact:

• 400+ Million members connected through our platform.
• 100+ Global Brands trust us to drive loyalty and brand devotion.
• 3-Time Winner of “Best Technology Innovation in Loyalty”.
• Global recognitions for Excellence in Loyalty Management under numerous categories.
• Recognised as a ‘Strong performer’ in The Forrester Wave™ Loyalty Platforms, Q4 2025.

Explore more about us at www.lji.io

What you will OWN:

• Build the infrastructure required for optimal extraction, transformation, and loading of data from various sources using SQL and AWS ‘big data’ technologies.
• Create and maintain optimal data pipeline architecture.
• Identify, design, and implement internal process improvements, automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Work with stakeholders, including the Technical Architects, Developers, Product Owners, and Executives, to assist with data-related technical issues and support their data infrastructure needs.
• Create tools for data management and data analytics that can assist them in building and optimizing our product to become an innovative industry leader.

You would make a GREAT FIT if you have:

• Have 2 to 5 years of relevant backend development experience, with solid expertise in Python.
• Possess strong skills in Data Structures and Algorithms, and can write optimized, maintainable code.
• Are familiar with database systems, and can comfortably work with PostgreSQL, as well as NoSQL solutions like MongoDB or DynamoDB.
• Hands-on experience using Cloud Dataware houses like AWS Redshift, GBQ, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift, and AWS Batch would be an added advantage.
• Have a solid understanding of ETL processes and tools and can build or modify ETL pipelines effectively.
• Have experience managing or building data pipelines and architectures at scale.
• Understand the nuances of data ingestion, transformation, storage, and analytics workflows.
• Communicate clearly and work collaboratively across engineering, product.

Why Choose US?

• This opportunity offers a dynamic and supportive work environment where you'll have the chance to not just collaborate with talented technocrats but also work with globally recognized brands, gain exposure, and carve your own career path.
• You will get to innovate and dabble in the future of technology -Enterprise Cloud Computing, Blockchain, Machine Learning, AI, Mobile, Digital Wallets, and much more.

· Strategy & Architecture: Collaborate with stakeholders to define end-to-end migration strategies, including data mapping, transformation, and validation rules.

· Technical Execution: Utilize tools like SQL DB, CSV2TCXML, IPS Upload, and ETL tools to migrate CAD and metadata.

· Customization: Develop custom migration solutions using BMIDE (Business Modeler IDE), ITK (Integration Toolkit), and SOA (Service Oriented Architecture).

· Project Leadership: Break down projects into manageable work packages, leading both onsite and offshore teams.

· Validation & Quality: Perform validation checks to ensure data integrity and accuracy post-migration.

· Integration Support: Manage CAD integrations (NX, Inventor, Creo) and PLM integrations (T4S, T4O, T4EA).

Key Skills:

Technical Skills

• Power BI Development: 4-5 years of hands-on experience developing Power BI reports, dashboards, and data models
• DAX: Strong proficiency in DAX (Data Analysis Expressions) for creating measures, calculated columns, and complex calculations
• Power Query / M Language: Expertise in data transformation and ETL processes using Power Query
• Data Modeling: Solid understanding of dimensional modeling, star schema, and data warehouse concepts
• SQL: Proficient in SQL for data extraction, manipulation, and querying relational databases
• Power BI Service: Experience with Power BI Service administration, workspace management, scheduled refreshes, and deployment pipelines
• Custom Visualizations: Experience creating and configuring custom visuals, including use of AppSource visuals and custom visual development using Power BI Visuals SDK
• API Integration: Hands-on experience with Power BI REST APIs for automating deployments, managing workspaces, and embedding reports
• Knowledge of data visualization best practices and UI/UX principles for dashboard design
• Experience with data source connectivity (SQL Server, Azure SQL, Oracle, SAP, Excel, APIs, web services)

Additional Required Qualifications

• Bachelor’s degree in computer science, Information Systems, Business Analytics, or related field
• Strong analytical and problem-solving abilities
• Excellent communication skills to work with both technical and non-technical stakeholders
• Ability to manage multiple projects and prioritize tasks effectively
• Detail-oriented with commitment to delivering high-quality work
• Client-facing experience with ability to gather requirements and present solutions

Preferred Qualifications

• Microsoft Power BI certification (PL-300 or equivalent)
• Experience with Azure ecosystem (Azure Data Factory, Azure Synapse Analytics, Azure SQL Database)
• Knowledge of other Microsoft BI tools (SSRS, SSAS, Excel Power Pivot)
• Familiarity with Python or R for advanced analytics integration
• Experience with Dataflows and incremental refresh strategies
• Understanding of API development for custom visuals or Power BI embedded solutions
• Experience working in Agile/Scrum development environments

JD - 

We are looking for a strong Data Engineer having hands on experience in building pipelines using Snowflake and DBT.

Key Responsibilities:

• Develop, maintain, and optimize data pipelines using DBT and SQL on Snowflake DB.
• Collaborate with data analysts, QA and business teams to build scalable data models.
• Implement data transformations, testing, and documentation within the DBT framework.
• Work on Snowflake for data warehousing tasks, including data ingestion, query optimization, and performance tuning.
• Use Python (preferred) for automation, scripting, and additional data processing as needed.

Required Skills:

• 6+ years of experience in building data engineering pipelines.
• Strong hands-on expertise with DBT and advanced SQL.
• Experience working with modern columnar/MPP data warehouses, preferably Snowflake.
• Knowledge of Python for data manipulation and workflow automation (preferred).
• Good understanding of data modeling concepts, ETL/ELT processes, and best practice.

Profile - Databricks Developer

Experience- 5+ years

Location- Bangalore (On site)

PF & BGV is Mandatory

Job Description: -

* Design, build, and optimize data pipelines and ETL/ELT workflows using Databricks and

Apache Spark (PySpark).

* Develop scalable, high performance data solutions using Spark distributed processing.

* Lead engineering initiatives focused on automation, performance tuning, and platform

modernization.

* Implement and manage CI/CD pipelines using Git-based workflows and tools such as

GitHub Actions or Jenkins.

* Collaborate with cross-functional teams to translate business needs into technical

solutions.

* Ensure data quality, governance, and security across all processes.

* Troubleshoot and optimize Spark jobs, Databricks clusters, and workflows.

* Participate in code reviews and develop reusable engineering frameworks.

* Should have knowledge of utilizing AI tools to improve productivity and support daily

engineering activities.

* Strong knowledge and hands-on experience in Databricks Genie, including prompt

engineering, workspace usage, and automation.

Required Skills & Experience:

* 5+ years of experience in Data Engineering or related fields.

* Strong hands-on expertise in Databricks (notebooks, Delta Lake, job orchestration).

* Deep knowledge of Apache Spark (PySpark, Spark SQL, optimization techniques).

* Strong proficiency in Python for data processing, automation, and framework

development.

* Strong proficiency in SQL, including complex queries, performance tuning, and analytical

functions.

* Strong knowledge of Databricks Genie and leveraging it for engineering workflows.

* Strong experience with CI/CD and Git-based development workflows.

* Proficiency in data modeling and ETL/ELT pipeline design.

* Experience with automation frameworks and scheduling tools.

* Solid understanding of distributed systems and big data concepts

Job Summary

We are seeking a skilled Data Engineer with 4+ years of experience in building scalable data pipelines and working with modern data platforms. The ideal candidate should have strong expertise in Python, SQL, and cloud-based data solutions, with hands-on experience in ETL/ELT processes and data warehousing.

Key Responsibilities

• Design, build, and maintain scalable data pipelines using Python
• Develop and optimize ETL/ELT workflows for data ingestion and transformation
• Work with structured and unstructured data from multiple sources
• Build and manage data warehouses/data lakes
• Perform data validation, cleansing, and quality checks
• Optimize SQL queries and improve data processing performance
• Collaborate with data analysts, data scientists, and business teams
• Implement data governance, security, and best practices
• Monitor pipelines and troubleshoot production issues

Required Skills

• Strong programming experience in Python (Pandas, NumPy, PySpark preferred)
• Excellent SQL skills (joins, window functions, performance tuning)
• Experience with ETL tools like Informatica, Talend, or DBT
• Hands-on experience with cloud platforms (Azure / AWS / GCP)
• Experience in data warehousing solutions like Snowflake, Redshift, BigQuery
• Knowledge of workflow orchestration tools like Apache Airflow
• Familiarity with version control tools like Git

Preferred Skills

• Experience with Big Data technologies (Spark, Hadoop)
• Knowledge of streaming tools like Kafka
• Exposure to CI/CD pipelines and DevOps practices
• Experience in data modeling (Star/Snowflake schema)
• Understanding of APIs and data integration

The AI Data Engineer will be responsible for designing, building, and operating scalable data pipelines and curated data assets that power machine learning, generative AI, and intelligent automation solutions in an SLA-driven managed services environment. This role focuses on data ingestion, transformation, governance, and operational reliability across cloud and hybrid environments enabling use cases such as knowledge retrieval (RAG), conversational AI, predictive analytics, and AI-assisted service management. The ideal candidate combines strong data engineering fundamentals with an understanding of AI workload requirements, including quality, lineage, privacy, and performance. 

Key Responsibilities 

•Design, build, and operate production-grade data pipelines that support AI/ML and generative AI workloads in managed services environments 

•Develop curated, analytics-ready datasets and data products to enable model training, grounding, feature generation, and AI search/retrieval 

•Implement data ingestion patterns for structured and unstructured sources (APIs, databases, files, event streams, documents) 

•Build and maintain transformation workflows with strong testing and validation 

•Enable Retrieval-Augmented Generation (RAG) by preparing document corpora, chunking strategies, metadata enrichment, and vector indexing patterns 

•Integrate data pipelines with application services 

•Support ITSM and enterprise workflow data needs, including ServiceNow data integration, CMDB/incident data quality improvements, and automation enablement 

•Implement observability for data pipelines (monitoring, alerting, SLAs/SLOs) and perform root cause analysis for pipeline failures or data quality incidents 

•Apply data governance and security best practices 

•Collaborate with ML Engineers, DevOps/SRE, and solution architects to operationalize end-to-end AI solutions 

•Contribute to reusable patterns, templates, and standards within the Bell Techlogix AI Center of Excellence 

Required Qualifications 

•Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience 

•5+ years of experience in data engineering, analytics engineering, or platform data operations 

•Strong proficiency in SQL and Python; experience with data modeling and dimensional concepts 

•Hands-on experience with Azure data services (e.g., Data Factory, Synapse, Databricks, Storage, Key Vault) or equivalent cloud tooling 

•Experience building reliable pipelines with scheduling, dependency management, and automated testing/validation 

•Experience supporting production data platforms with incident management, troubleshooting, and root cause analysis 

•Understanding of data security, privacy, and governance principles in enterprise environments 

Preferred Qualifications 

•Experience enabling AI/ML workloads: feature engineering, training data preparation, and integration with Azure Machine Learning 

•Experience with unstructured data processing for generative AI 

•Familiarity with vector databases or vector search and RAG patterns 

•Experience with event streaming and messaging 

•Familiarity with ServiceNow data model and integration patterns (Table API, export, CMDB/ITSM reporting) 

•Relevant certifications (Microsoft Azure Data Engineer, Azure AI Engineer, Databricks) 

Profile - Databricks Developer

Experience- 5+ years

Location- Bangalore (On site)

PF & BGV is Mandatory

Job Description: -

* Design, build, and optimize data pipelines and ETL/ELT workflows using Databricks and Apache Spark (PySpark).

* Develop scalable, high performance data solutions using Spark distributed processing.

* Lead engineering initiatives focused on automation, performance tuning, and platform modernization.

* Implement and manage CI/CD pipelines using Git-based workflows and tools such as GitHub Actions or Jenkins.

* Collaborate with cross-functional teams to translate business needs into technical solutions.

* Ensure data quality, governance, and security across all processes.

* Troubleshoot and optimize Spark jobs, Databricks clusters, and workflows.

* Participate in code reviews and develop reusable engineering frameworks.

* Should have knowledge of utilizing AI tools to improve productivity and support daily engineering activities.

* Strong knowledge and hands-on experience in Databricks Genie, including prompt engineering, workspace usage, and automation

. Required Skills & Experience:

* 5+ years of experience in Data Engineering or related fields.

* Strong hands-on expertise in Databricks (notebooks, Delta Lake, job orchestration).

* Deep knowledge of Apache Spark (PySpark, Spark SQL, optimization techniques).

* Strong proficiency in Python for data processing, automation, and framework development.

* Strong proficiency in SQL, including complex queries, performance tuning, and analytical functions.

* Strong knowledge of Databricks Genie and leveraging it for engineering workflows.

* Strong experience with CI/CD and Git-based development workflows. * Proficiency in data modeling and ETL/ELT pipeline design.

* Experience with automation frameworks and scheduling tools.

* Solid understanding of distributed systems and big data concepts

Who are we ?

Searce means ‘a fine sieve’ & indicates ‘to refine, to analyze, to improve’. It signifies our way of working: To improve to the finest degree of excellence, ‘solving for better’ every time. Searcians are passionate improvers & solvers who love to question the status quo.

The primary purpose of all of us, at Searce, is driving intelligent, impactful & futuristic business outcomes using new-age technology. This purpose is driven passionately by HAPPIER people who aim to become better, everyday.

Tech Superpowers

End-to-End Ecosystem Thinker: You build modular, reusable data products across ingestion, transformation (ETL/ELT), and consumption layers. You ensure the entire data lifecycle is governed, scalable, and optimized for high-velocity delivery.

The MDS Architect. You reimagine business with the Modern Data Stack (MDS) to deliver Data Mesh implementations and real value. You treat every dataset as a measurable "Data Product with a clear focus on ROI and time-to-insight.

Distributed Compute & Scale Savant: You craft resilient architectures that survive petabyte scale volume and data skew without "breaking the bank. You prove your designs with cost-performance benchmarks, not just slideware.

Al-Ready Orchestrator: You engineer the bridge between structured data and Unstructured/Vector stores. By mastering pipelines for RAG models and GenAl, you turn raw data into the fuel for intelligent, automated workflows.

The Quality Craftsman (Builder @ Heart): You are an outcome-focused leader who lives in the code. From embedding GDPR/PII privacy-by-design to optimizing SQL, Python, and Spark daily, you ensure integrity is baked into every table

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.

Al-Native Workflow: You don't just build for Al you build with Al. You must be proficient in using Al coding assistants (e.g.. GitHub Copilot) to accelerate your delivery and have a track record of building the data foundations required for Generative Al.

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.

The "Solver" Mindset: A track record of solving 'impossible data problems-whether it's fixing massive data skew, optimizing spiraling cloud costs, or architecting 99.9% available data services.

Job Title: Lead Data Architect (AI & Cloud)

Company: Risosu Consulting

About the Role

Risosu Consulting is hiring a Lead Data Architect / Crew Manager for one of our global clients in the Cloud, Data & AI space. This role focuses on designing scalable data architectures and driving AI-led transformation across modern cloud platforms.

Key Responsibilities

• Design data strategies, architectures, and scalable cloud solutions
• Build and optimize data pipelines, data lakes, and warehouses
• Collaborate with cross-functional teams to enable AI/ML use cases
• Lead client engagements and translate business needs into data solutions
• Mentor and manage a team of consultants as a Crew Manager

Requirements

• 5+ years of experience in Data Architecture / Engineering
• Strong expertise in cloud platforms (GCP/AWS/Azure)
• Experience with data modeling, ETL, and data governance
• Exposure to tools like BigQuery, dbt, Airbyte, or Power BI
• Strong communication skills and stakeholder management

Why Join via Risosu?

• Opportunity to work on high-impact global projects
• Fast-growing, entrepreneurial environment
• Clear growth path with learning & certification support
• Work with cutting-edge Cloud, Data & AI technologies

If you’re passionate about building scalable data systems and leading teams, let’s connect.

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.

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’

Job Title : AWS Data Engineer

Experience : 4+ Years

Location : Bengaluru (HSR – Hybrid, 3 Days WFO)

Notice Period : Immediate Joiner

💡 Role Overview :

We are looking for a skilled AWS Data Engineer to design, build, and scale modern data platforms. The role involves working with AWS-native services, Python, Spark, and DBT to deliver secure, scalable, and high-performance data solutions in an Agile environment.

🔥 Mandatory Skills :

Python, SQL, Spark, AWS (S3, Glue, EMR, Redshift, Athena, Lambda), DBT, ETL/ELT pipeline development, Airflow/Step Functions, Data Lake (Parquet/ORC/Iceberg), Terraform & CI/CD, Data Governance & Security

🚀 Key Responsibilities :

• Design, build, and optimize ETL/ELT pipelines using Python, DBT, and AWS services
• Develop and manage scalable data lakes on S3 using formats like Parquet, ORC, and Iceberg
• Build end-to-end data solutions using Glue, EMR, Lambda, Redshift, and Athena
• Implement data governance, security, and metadata management using Glue Data Catalog, Lake Formation, IAM, and KMS
• Orchestrate workflows using Airflow, Step Functions, or AWS-native tools
• Ensure reliability and automation via CloudWatch, CloudTrail, CodePipeline, and Terraform
• Collaborate with data analysts and data scientists to deliver actionable insights
• Work in an Agile environment to deliver high-quality data solutions

✅ Mandatory Skills :

• Strong Python (including AWS SDKs), SQL, Spark
• Hands-on experience with AWS data stack (S3, Glue, EMR, Redshift, Athena, Lambda)
• Experience with DBT and ETL/ELT pipeline development
• Workflow orchestration using Airflow / Step Functions
• Knowledge of data lake formats (Parquet, ORC, Iceberg)
• Exposure to DevOps practices (Terraform, CI/CD)
• Strong understanding of data governance and security best practices
• Minimum 4–7 years in Data Engineering (3+ years on AWS)

➕ Good to Have :

• Understanding of Data Mesh architecture
• Experience with platforms like Data.World
• Exposure to Hadoop / HDFS ecosystems

🤝 What We’re Looking For :

• Strong problem-solving and analytical skills
• Ability to work in a collaborative, cross-functional environment
• Good communication and stakeholder management skills
• Self-driven and adaptable to fast-paced environments

📝 Interview Process :

1. Online Assessment
2. Technical Interview
3. Fitment Round
4. Client Round

Job Title: Data Developer Lead

Experience: 10+ Years

Location: Gurgaon (Onsite)

Work Model: Hybrid

Role Overview:

We are looking for a highly experienced Data Developer with 10+ years of expertise in designing, developing, and managing scalable data solutions. The ideal candidate will have strong experience in data engineering, ETL processes, and database management, with the ability to work in a hybrid onsite environment in Gurgaon.

Key Responsibilities:

• Design, develop, and maintain robust data pipelines and ETL processes
• Build scalable data architectures and optimize data workflows
• Work with large datasets to ensure data accuracy, integrity, and availability
• Develop and manage data warehouses and data lakes
• Collaborate with cross-functional teams including Data Science, Analytics, and Engineering
• Optimize database performance and troubleshoot data-related issues
• Ensure data security, governance, and compliance standards are followed
• Automate data processes and improve system efficiency
• Mentor junior team members and provide technical guidance

Required Skills & Qualifications:

• 10+ years of experience in Data Engineering / Data Development
• Strong proficiency in SQL and database technologies (e.g., PostgreSQL, MySQL, Oracle)
• Hands-on experience with ETL tools (Informatica, Talend, Apache NiFi, etc.)
• Experience with big data technologies (Hadoop, Spark, Hive)
• Proficiency in programming languages like Python, Java, or Scala
• Experience with cloud platforms (AWS, Azure, or GCP)
• Strong understanding of data warehousing concepts (Snowflake, Redshift, BigQuery, etc.)
• Experience with data modeling and schema design
• Familiarity with workflow orchestration tools (Airflow, etc.)

Good to Have:

• Experience in real-time data streaming (Kafka, Flink)
• Exposure to DevOps practices and CI/CD pipelines
• Knowledge of data governance and data quality frameworks
• Experience working in Agile environments

Soft Skills:

• Strong problem-solving and analytical skills
• Excellent communication and stakeholder management
• Ability to work independently and in a collaborative team

Why Join Us?

• Opportunity to work on large-scale data systems
• Collaborative and innovation-driven environment
• Flexible hybrid work model

About the Role:

We are seeking a skilled Data Engineer to join our growing AdTech team. In this role, you will design, build, and maintain high-performance ETL pipelines and large-scale data processing systems. You will work with massive datasets and distributed frameworks to power Adsremedy’s data-driven advertising solutions across Programmatic, In-App, CTV, and DOOH platforms.

What You’ll Do:

• Design, develop, and maintain scalable ETL pipelines on self-managed infrastructure
• Process and optimize large-scale datasets (terabytes of data) with high reliability and performance
• Build robust data processing workflows using Apache Spark (preferred) and/or Apache Flink
• Integrate, clean, and transform data from multiple internal and external sources
• Partner closely with data scientists, analysts, and business stakeholders to enable actionable insights
• Monitor, troubleshoot, and optimize data pipelines for operational excellence
• Ensure data quality, consistency, and performance across all data workflows
• Participate in code reviews and uphold best practices in data engineering
• Collaborate with QA teams to deliver production-ready, reliable systems
• Mentor junior engineers and promote knowledge sharing within the team
• Stay current with emerging data engineering tools, frameworks, and industry trends

What You’ll Need:

• 2+ years of experience building ETL pipelines using Apache Spark and/or Apache Flink
• Hands-on experience with big data caching solutions such as ScyllaDB, Aerospike, or similar
• Strong understanding of data lake architectures and tools like Delta Lake
• Proven experience handling terabytes of data in distributed environments
• Proficiency in Scala, Python, or Java
• Experience working with cloud data platforms (AWS S3, Azure Data Lake, Google BigQuery)
• Strong knowledge of SQL, data modeling, and data warehousing concepts
• Familiarity with Git and CI/CD workflows
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment

Nice to Have

• Experience with Apache Kafka for real-time data streaming
• Familiarity with Apache Airflow or similar orchestration tools

• 10+ years of software development experience
• 3+ years in a technical leadership role
• Strong expertise in Python and SQL
• Experience building scalable APIs and backend systems
• Solid understanding of database design and performance tuning
• Experience with Azure cloud services (AWS familiarity preferred)
• Working knowledge of ML/AI integration in enterprise systems
• Experience in client-facing or consulting environments preferred
• Experience with Databricks or modern data platforms
• Exposure to ETL tools such as Talend
• Experience with BI tools (e.g., Power BI)
• Exposure to regulated domains such as Pharma, Healthcare

Job Title: Data Engineer

About the Role

We are looking for a highly motivated Data Engineer to join our growing team and play

a critical role in shaping the data foundation of different software platforms. This role sits

at the intersection of data engineering, product, and business stakeholders, and is

responsible for building reliable data pipelines, delivering actionable insights, and

ensuring data quality across systems.

You will work closely with internal teams and external partners to translate business

requirements into scalable data solutions, while maintaining high standards for data

integrity, performance, and usability.

Key Responsibilities

Data Engineering & Architecture

 Design, build, and maintain scalable data pipelines and ETL/ELT processes

 Develop and optimize data models in PostgreSQL and cloud-native

architectures

 Work within AWS ecosystem (e.g., S3, Lambda, RDS, Glue, Redshift, etc.) to

support data workflows

 Ensure efficient ingestion and processing of large-scale datasets

Business & Partner Integration

 Collaborate directly with business stakeholders and external partners to

gather requirements and deliver reporting solutions

 Translate ambiguous business needs into structured data models and

dashboards

 Integrate with third-party APIs and other external data sources

Data Quality & Governance

 Implement robust data validation, monitoring, and QA processes

 Ensure consistency, accuracy, and reliability of data across the platform

 Troubleshoot and resolve data discrepancies proactively

Reporting & Analytics Enablement

 Build datasets and pipelines that power dashboards and reporting tools

 Support internal teams with ad hoc analysis and data requests

 Partner with product and engineering teams to embed data into the SaaS product experience

Performance & Scalability

 Optimize queries, pipelines, and storage for performance and cost efficiency

 Continuously improve system scalability as data volume and complexity grow

Required Qualifications

 3–6+ years of experience in Data Engineering or related role

 Strong proficiency in Python for data processing and scripting

 Advanced experience with PostgreSQL (query optimization, schema design)

 Hands-on experience with AWS data architecture (S3, RDS, Lambda, Glue,

Redshift, etc.)

 Experience integrating with external APIs

 Solid understanding of ETL/ELT pipelines, data modeling, and warehousing

concepts

 Experience working cross-functionally with business stakeholders

Preferred Qualifications

 Experience in AdTech, eCommerce, or SaaS platforms

 Familiarity with BI tools (e.g., Looker, Tableau, Power BI)

 Experience with workflow orchestration tools (e.g., Airflow)

 Understanding of data governance and compliance best practices

 Exposure to real-time or streaming data pipelines

What We’re Looking For

 Strong problem-solver who can operate in a fast-paced, ambiguous

environment

 Ability to balance technical depth with business context

 Excellent communication skills — able to work directly with non-technical

stakeholders

 Ownership mindset with a focus on execution and quality

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.

Note-“Urgently Hiring – Immediate Joiners Preferred”

Data Engineering

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
• Mandatory (Experience 1) – Must have 6+ years of hands-on experience in Data Engineering, with strong ownership of end-to-end data pipeline development.
• Mandatory (Experience 2) – Must have strong experience in ETL/ELT pipeline design, transformation logic, and data workflow orchestration.
• Mandatory (Experience 3) – 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.
• Mandatory (Experience 4) – Must have working experience on any cloud platform: GCP (preferred), AWS, or Azure, including object storage (GCS, S3, ADLS).
• Mandatory (Core Skill 1) – Must have strong SQL skills with experience in writing complex queries and optimizing performance.
• Mandatory (Core Skill 2) – Must have programming experience in Python and/or SQL for data processing.
• Mandatory (Core Skill 3) – Must have experience in building and maintaining scalable data pipelines and troubleshooting data issues.
• Preferred (Experience 1) – Exposure to data migration projects and/or data mesh architecture concepts.
• Preferred (Skill 1) – Experience with Spark/PySpark or large-scale data processing frameworks.
• Preferred (Company) – Experience working in product-based companies or data-driven environments.
• Preferred (Education) – Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

.

Job Description & Specification: 

Post Title: Data Engineer

Work Mode: Kochi Onsite - UK Time zone

Role Overview: 

We are seeking a talented and experienced Data Engineer to join our team. The ideal candidate will have expertise in technologies such as Metabases, Dbt, Stitch, Snowflake, Avo, and MongoDB. As a Data Engineer, you will play a crucial role in designing, developing, and maintaining our data infrastructure to support our analytics and data-driven decision-making processes.

Responsibilities:

• Designing, developing and implementing scalable data pipelines and ETL processes using tools such as Stitch and Dbt to ingest, transform, and load data from various sources into our data warehouse (Snowflake).
• Implement data modeling best practices and standards using Dbt to create and manage data models for reporting and analytics.
• Collaborating with cross-functional teams to understand data requirements and deliver solutions that meet business needs.
• Develop and maintain dashboards and visualizations in Metabases to enable self-service analytics and data exploration for internal teams.
• Building and optimizing ETL processes to ensure data quality and integrity.
• Optimizing data processing and storage solutions for performance, scalability and reliability, leveraging cloud-based technologies.
• Implementing monitoring and alerting systems to proactively identify and address data issues.
• Implementing data quality checks and monitoring processes to ensure the accuracy, completeness, and integrity of data.
• Managing and optimizing databases (like MongoDB for performance and scalability).
• Developing and maintaining documentation, best practices, and standards for data engineering processes and workflows.
• Stay up to date with emerging technologies and trends in data engineering, machine learning, and analytics, and evaluate their potential impact on data strategy and architecture.

Requirements:

• Bachelor's or Master's degree in Computer Science.
• Minimum of 4 years of experience working as a data engineer with expertise in Metabases, Dbt, Stitch, Snowflake, Avo, MongoDB.
• Strong programming skills in languages like Python, and experience with SQL and database technologies (e.g., PostgreSQL, MySQL, MongoDB).
• Hands-on experience with data integration tools (e.g., Stitch), data modeling tools (e.g., Dbt), and BI platforms (e.g., Metabases).
• Experience with cloud platforms such as AWS.
• Strong understanding of data modeling concepts, database design, and data warehousing principles
• Experience with big data technologies and frameworks (e.g., Hadoop, Spark, Kafka) and cloud-based data platforms (e.g., AWS EMR, Azure Databricks, Google BigQuery).
• Familiarity with data integration tools, ETL processes, and workflow orchestration tools (e.g., Apache Airflow, Apache NiFi).
• Excellent problem-solving skills and attention to detail.
• Strong communication skills with the ability to work effectively in a global team environment.
• Experience in the education or Edtech industry is a plus.
• Knowledge of Avo for schema management and versioning will be an added advantage.
• Familiarity with machine learning algorithms, data science workflows, and analytics tools (e.g., TensorFlow, PyTorch, scikit-learn, Tableau).
• Knowledge of distributed computing concepts and containerization technologies.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Certifications in cloud computing (e.g., AWS Certified Developer, Google Cloud Professional Data Engineer) or data engineering (e.g., Databricks Certified Associate Developer) are desirable.

Benefits:

• Competitive salary and bonus structure based on performance and achievement of goals.
• Comprehensive benefits package including medical insurance.

Join us in shaping the future of technology by applying your expertise as a Data Engineer. If you are passionate about driving innovation and delivering impactful solutions, we invite you to be part of our dynamic team. Apply now!!

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

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

Description

Power BI JD

Mandatory:

• 5+ years of Power BI Report development experience.

• Building Analysis Services reporting models.

• Developing visual reports, KPI scorecards, and dashboards using Power BI desktop.

• Connecting data sources, importing data, and transforming data for Business intelligence.

• Analytical thinking for translating data into informative reports and visuals.

• Capable of implementing row-level security on data along with an understanding of application security layer models in Power BI.

• Should have an edge over making DAX queries in Power BI desktop.

• Expert in using advanced-level calculations on the data set.

• Responsible for design methodology and project documentaries.

• Should be able to develop tabular and multidimensional models that are compatible with data warehouse standards.

• Very good communication skills must be able to discuss the requirements effectively with the client teams, and with internal teams.

• Experience working with Microsoft Business Intelligence Stack having Power BI, SSAS, SSRS, and SSIS

• Mandate to have experience with BI tools and systems such as Power BI, Tableau, and SAP.

• Must have 3-4years of experience in data-specific roles.

• Have knowledge of database fundamentals such as multidimensional database design, relational database design, and more

• Knowledge of all the Power BI products (Power Bi premium, Power BI server, Power BI services, Powerquery etc)

• Grip over data analytics

• Interact with customers to understand their business problems and provide best-in-class analytics solutions

• Proficient in SQL and Query performance tuning skills

• Understand data governance, quality and security and integrate analytics with these corporate platforms

• Attention to detail and ability to deliver accurate client outputs

• Experience of working with large and multiple datasets / data warehouses

• Ability to derive insights from data and analysis and create presentations for client teams

• Experience with performance optimization of the dashboards

• Interact with UX/UI designers to create best in class visualization for business harnessing all product capabilities.

• Resilience under pressure and against deadlines.

• Proactive attitude and an open outlook.

• Strong analytical problem-solving skills

• Skill in identifying data issues and anomalies during the analysis

• Strong business acumen demonstrated an aptitude for analytics that incite action

• Ability to execute on design requirements defined by business

• Ability to understand required Power BI functionality from wireframes/ requirement documents

• Ability to architect and design reporting solutions based on client needs.

• Being able to communicate with internal/external customers, desire to develop communication and client-facing skills.

• Ability to seamlessly work with MS Excel working knowledge of pivot table and related functions

Good to have:

• Experience in working with Azure and connecting synapse with Tableau

• Demonstrate strength in data modelling, ETL development, and data warehousing

• Knowledge of leading large-scale data warehousing and analytics projects using Azure, Synapse, MS SQL DB

• Good knowledge of building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

• Good to have knowledge of Supply Chain Domain.

Blue Owls Solutions is looking for a mid-level Azure Data Engineer with approximately 4 years of hands-on experience to join our growing data team. In this role, you will design, build, and maintain scalable data pipelines and architectures that power business-critical analytics and reporting. You'll work closely with cross-functional teams to transform raw data into reliable, high-quality datasets that drive decision-making across the organization.

Required Skills

• 4+ years of professional experience as a Data Engineer or in a similar data-focused role
• Strong proficiency in SQL for data manipulation, querying, and performance optimization
• Hands-on experience with PySpark for large-scale data processing and transformation
• Solid working knowledge of the Microsoft Azure ecosystem (Azure Data Factory, Azure Data Lake, Azure Synapse, etc.)
• Experience with Microsoft Fabric for end-to-end data analytics workflows
• Ability to design and implement robust data architectures including data warehouses, lakehouses, and ETL/ELT frameworks
• Strong coding and scripting skills with Python
• Proven problem-solving ability with a knack for debugging complex data issues and optimizing pipeline performance
• Understanding of data modeling concepts, dimensional modeling, and data governance best practices

Interview Process

• Take-Home Assessment
• 60-Minute Technical Interview
• Culture Fit Round

Preferred Skills & Certifications

• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
• Microsoft Certified: Fabric Data Engineer Associate (DP-700)
• Experience with CI/CD practices for data pipelines
• Familiarity with version control systems such as Git
• Exposure to real-time streaming data solutions
• Experience working in Agile or Scrum environments
• Strong communication skills with the ability to translate technical concepts for non-technical stakeholders

What We Offer

• Competitive salary and performance-based bonuses
• Flexible hybrid options
• Opportunities for professional development, training, and certification sponsorship
• A collaborative, innovation-driven team culture
• Paid time off and company holidays

Position Title : Senior Data Engineer(Founding Member) - Insurtech StartUp

Location : Hyderabad(Onsite)

Immediate to 15 days Joiners

Experience : 5+ to 13 Years

Role Summary

We are looking for a Senior Data Engineer who will play a foundational role in:

• Client onboarding from a data perspective
• Understanding complex insurance data flows
• Designing secure, scalable ingestion pipelines
• Establishing strong data modeling and governance standards

This role sits at the intersection of technology, data architecture, security, and business onboarding.

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Key Responsibilities

• Lead end-to-end data onboarding for new clients and partners, working closely with business and product teams to understand client systems, data formats, and migration constraints
• Define and implement data ingestion strategies supporting multiple sources and formats, including CSV, XML, JSON files, and API-based integrations
• Design, build, and operate robust, scalable ETL/ELT pipelines, supporting both batch and near-real-time data processing
• Handle complex insurance-domain data including Contracts, Claims, Reserves, Cancellations, and Refunds
• Architect ingestion pipelines with security-by-design principles, including secure credential management (keys, secrets, tokens), encryption at rest and in transit, and network-level controls where required
• Enforce role-based and attribute-based access controls, ensuring strict data isolation, tenancy boundaries, and stakeholder-specific access rules
• Design, maintain, and evolve canonical data models that support operational workflows, reporting & analytics, and regulatory/audit requirements
• Define and enforce data governance standards, ensuring compliance with insurance and financial data regulations and consistent definitions of business metrics across stakeholders
• Build and operate data pipelines on a cloud-native platform, leveraging distributed processing frameworks (Spark / PySpark), data lakes, lakehouses, and warehouses
• Implement and manage orchestration, monitoring, alerting, and cost-optimization mechanisms across the data platform
• Contribute to long-term data strategy, platform architecture decisions, and cost-optimization initiatives while maintaining strict security and compliance standards

Required Technical Skills

• Core Stack: Python, Advanced SQL(Complex joins, window functions, performance tuning), Pyspark
• Platforms: Azure, AWS, Data Bricks, Snowflake
• ETL / Orchestration: Airflow or similar frameworks
• Data Modeling: Star/Snowflake schema, dimensional modeling, OLAP/OLTP
• Visualization Exposure: Power BI
• Version Control & CI/CD: GitHub, Azure Devops, or equivalent
• Integrations: APIs, real-time data streaming, ML model integration exposure

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 5+ years of experience in data engineering or similar roles
• Strong ability to align technical solutions with business objectives
• Excellent communication and stakeholder management skills

What We Offer

• Direct collaboration with the core US data leadership team
• High ownership and trust to manage the function end-to-end
• Exposure to a global environment with advanced tools and best practices