50+ SQL Jobs in India

What You'll Do

• Design, build, and maintain web and backend systems using Python and Node.js
• Develop custom workflows and automation solutions that streamline business processes
• Conduct code reviews, troubleshoot and resolve bugs, and manage database performance and integrity
• Partner with cross-functional teams to gather requirements and deliver effective solutions
• Write clean, maintainable, well-documented code that meets high quality standards
• Mentor and support junior developers through guidance and knowledge sharing

What We're Looking For

• 2–5 years of professional software development experience
• Strong proficiency in Python, Node.js, and REST API design and development
• Hands-on experience with workflow and automation tools
• Self-motivated with excellent communication skills and a collaborative mindset

Why You'll Love This Role

• Take full ownership of projects from concept through delivery
• Grow as a leader by mentoring and developing junior engineers
• Work with direct access to stakeholders and leadership, with real influence on decisions

Key responsibilities:

Design, develop, and maintain database schemas, stored procedures, views, and queries in SQL Server and MySQL.

• Identify and resolve query performance bottlenecks using execution plans, indexing strategies, and tuning techniques.

• Conduct regular database health checks and performance reviews to ensure optimal operation.

• Collaborate with development and operations teams to support application data requirements.

• Write and optimize complex SQL scripts to meet business and operational needs.

• Support the DBA Team Lead with day-to-day database operations and incident resolution.

• Assist in monitoring database availability, integrity, and backups.

• Document database structures, procedures, and changes in a clear and organized manner.

• Implement best practices for data storage, retrieval, and processing efficiency.

• Contribute to the continuous improvement of database standards and internal processes.

• Identify and effectively prioritize situations requiring urgent attention.

• Stay current with system information, database technologies, changes, and updates.

• Experience with cloud-managed databases (e.g., Microsoft Azure SQL Database, Amazon RDS) and understanding of scaling, cost optimization, and high availability in cloud environments.

• Hands-on exposure to database automation and CI/CD practices (schema versioning, deployment pipelines, Infrastructure as Code).

• Strong knowledge of high availability and disaster recovery design, including replication, failover, and defined RPO/RTO ownership.

• Familiarity with database security best practices (encryption, access control, auditing, and protection of sensitive/regulated data).

• Experience with monitoring and observability tools, with a proactive approach to performance tuning and alerting.

• Scripting ability (PowerShell, Python, or Bash) to automate routine database operations and reduce manual effort.

• Experience with database migrations, version upgrades, or modernization initiatives (on-prem to cloud or legacy to current platforms).

• Ability to operate in a DevOps-oriented environment, partnering closely with engineering teams and owning database performance tied to application SLA.

• Articulated English skills, both written and spoken.

• Proficiency in T-SQL and/or standard SQL.

• Ability to multi-task and adjust priorities quickly in a fast-paced environment.

• Ability to research and implement solutions using available technical resources.

• Strong analytical and problem-solving skills with attention to detail.

• Ability to clearly communicate technical concepts to non-technical stakeholders.

• Advanced knowledge of database performance tuning and query optimization.

• Familiarity with cloud database platforms such as Microsoft Azure SQL, AWS RDS, or equivalent.

• Experience with database deployment automation and CI/CD pipelines. 

• Understanding of high availability, disaster recovery, and data protection strategies.

• Working knowledge of database monitoring and performance management tools.

• Basic scripting skills (PowerShell, Python, or Bash) for automation. 

• Awareness of data security and compliance considerations in regulated environments.

Forward Deployed Engineer (FDE) – KnackLabs.ai

As a Forward Deployed Engineer at knacklabs.ai, you will sit at the intersection of engineering and customer success. You'll embed directly with customer teams to understand their workflows, rapidly prototype and ship solutions using our platform, and turn those learnings into product improvements. This role is ideal for engineers who want high ownership, fast feedback loops, and direct exposure to how their code changes a customer's business.

What you will own

1. Customer embedding
2. Work directly with customers to understand their business processes, pain points, technical environments, and existing ERP/application landscape.
3. Solution building
4. Design, build, and deploy custom integrations, workflows, and applications on top of the knacklabs.ai platform.
5. Product feedback loop
6. Turn one-off customer builds into reusable, generalizable features by working closely with the core product and engineering teams.
7. Rapid prototyping
8. Write production-quality code under real deadlines, balancing speed with maintainability.
9. Technical troubleshooting
10. Debug issues across the stack, from data pipelines to APIs to front-end integrations, in live customer environments.
11. Ongoing ownership
12. Own the technical relationship with select customers post-deployment, ensuring solutions remain stable and scale with their needs.
13. Travel
14. Travel to customer sites as needed, expected occasionally and varying by account.

What we need from you

1. Three or more years of professional software engineering experience, ideally including customer-facing or implementation work.
2. Strong proficiency in at least one backend language (Python, Node.js, Go, or similar) and comfort working across a full stack.
3. Experience with REST/GraphQL APIs, databases (SQL/NoSQL), and cloud platforms (AWS, GCP, or Azure).
4. Proven experience building and deploying AI-driven solutions within enterprise application ecosystems, including ERP integrations, workflow automation pipelines, and end-to-end product development, with a track record of hands-on stakeholder engagement across technical and business teams.
5. Hands-on experience with ERP systems such as ERPNext/Frappe, SAP, Oracle ERP, Microsoft Dynamics/Navision/Business Central, Odoo, or similar enterprise ERP platforms, including experience with ERP implementation, customization, workflow/module modifications, integrations, or building applications on top of ERP systems, is strongly preferred.
6. Demonstrated ability to work independently in ambiguous, fast-changing environments.
7. Strong communication skills. You can explain technical tradeoffs clearly to both engineers and non-technical stakeholders.
8. A bias toward action. You are comfortable shipping a working solution today rather than a perfect one next month.

Job Summary

We are seeking an experienced Integration Support Engineer with 2+ years of experience in enterprise integration and production support. This role will act as the complete owner of the customer support board — managing, triaging, and resolving support tickets end to end while coordinating with engineering, product, and implementation teams. The ideal candidate has strong hands-on experience with Boomi or another iPaaS platform, deep working knowledge of databases and REST APIs, and a track record of rigorous testing and validation. Experience with Intapp Integration Builder is a plus.

Work Hours: 6:00 PM – 5:00 AM, with flexible breaks during the shift.

Key Responsibilities

• Own the customer support board end to end — triaging incoming tickets, managing priority and status, and driving each issue through to resolution.

• Serve as the frontline point of contact for customers on integration issues, providing clear, timely communication throughout the life of a ticket.

• Debug and troubleshoot integrations built on Boomi or other iPaaS platforms, performing root-cause analysis and resolving incidents within SLAs.

• Write, optimize, and troubleshoot SQL queries against production and staging databases for data validation, reconciliation, and issue investigation.

• Work extensively with REST/SOAP APIs, FTP/SFTP, and data formats such as JSON and XML to diagnose and resolve integration failures.

• Test and validate reported issues, including reproducing defects, verifying fixes, and confirming resolution before closing tickets.

• Participate in integration design and enhancement work, contributing to the build and improvement of existing integration processes.

• Take up new development and change requests, following SDLC practices — design, build, test, and deploy — to release changes safely to production.

• Work across internal teams — engineering, product, and implementation — to triage incoming issues, determine ownership, and coordinate resolution.

• Collaborate closely with engineering, product, and implementation teams to resolve both technical issues (database, integration, and server-side) and business/process issues.

• Stay flexible and continuously build cross-functional knowledge, since resolving tickets often requires learning new systems and business workflows on the fly.

• Maintain technical documentation, support guides, and troubleshooting procedures.

Qualifications:

• Bachelor's degree in Computer Science, IT, or a related field.

• 2+ years of experience in integration engineering, integration support, or a similar role.

• Hands-on experience with Boomi or another iPaaS platform.

• Strong, demonstrable skills in SQL and database troubleshooting — this role requires day-to-day, hands-on database work.

• Strong REST/SOAP API knowledge, including testing, debugging, and validating API-based integrations.

• Solid experience with structured testing and validation practices for integration issues.

• Good understanding of integration patterns, cloud technologies, and production support.

• Strong analytical, communication, and stakeholder-management skills.

• Ability to work flexibly across engineering, product, and implementation stakeholders, and to quickly learn new systems and domains.

• Willingness and ability to work the required shift: 6:00 PM – 5:00 AM.

Preferred Skills

• Boomi or relevant iPaaS certification.

• Experience with Intapp Integration Builder.

• Knowledge of Azure Functions, Logic Apps, and other Azure services.

• Experience with monitoring, logging, and integration observability.

What We Offer

Competitive salary and benefits, work-from-home flexibility, a dynamic work environment, and opportunities for professional growth while working on enterprise-grade integrations.

About the Role

We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and AI-assisted software development using Cursor. The role is suited for an engineer who can work directly with clients and internal teams to understand business problems, rapidly build solutions, and take them from prototype to production.

The ideal candidate should have strong expertise in Python, SQL, Databricks, PySpark, data engineering, APIs, and modern AI-assisted development workflows, along with excellent problem-solving and client-facing skills.

Key Responsibilities

Forward Deployed Engineering

• Work directly with clients and stakeholders to understand business and technical requirements.
• Translate business problems into scalable technical and data solutions.
• Rapidly prototype, test, iterate, and productionize solutions.
• Collaborate with engineering, data, AI, and delivery teams to implement customer solutions.
• Troubleshoot production issues and continuously improve deployed solutions.
• Act as a technical bridge between clients and internal engineering teams.

Databricks & Data Engineering

• Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
• Build and optimize ETL/ELT and data processing pipelines.
• Work with Databricks Lakehouse, Delta Lake, Unity Catalog, and Databricks Workflows.
• Develop data ingestion and transformation pipelines for structured and semi-structured data.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.

Cursor & AI-Assisted Development

• Use Cursor and AI-assisted development workflows to accelerate software development, debugging, refactoring, and documentation.
• Effectively use AI coding assistants to understand existing codebases and develop new features.
• Apply appropriate engineering judgment to review, validate, test, and secure AI-generated code.
• Use AI-assisted development for rapid prototyping and proof-of-concept development.
• Work with modern AI/LLM APIs and tools where required for customer solutions.
• Stay current with emerging AI-assisted software engineering practices.

Production & Deployment

• Develop production-ready applications, APIs, and data pipelines.
• Work with Git, CI/CD, APIs, containers, and cloud environments.
• Monitor application and pipeline performance and resolve production issues.
• Ensure solutions meet requirements for scalability, security, reliability, and maintainability.
• Collaborate with Data Scientists and ML Engineers to integrate AI/ML capabilities into production systems.

Required Skills & Experience

• 4+ years of experience in Software Engineering, Data Engineering, AI Engineering, or a related field.
• Strong hands-on experience with Databricks.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Delta Lake and Lakehouse architecture.
• Experience building production-grade data pipelines.
• Hands-on experience with Cursor or similar AI-powered coding assistants.
• Strong understanding of REST APIs and system integrations.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Strong debugging, problem-solving, and analytical skills.
• Excellent communication and client-facing abilities.

Preferred Skills

• Experience with Databricks Unity Catalog, Workflows, and MLflow.
• Experience with Generative AI / LLM applications.
• Knowledge of Claude, OpenAI, Azure OpenAI, or other LLM platforms.
• Experience with RAG, vector databases, embeddings, or AI agents.
• Experience with Docker, Kubernetes, and CI/CD.
• Experience in a consulting, customer-facing engineering, or professional services environment.
• Exposure to Agile/Scrum methodologies.

Key Competencies

• Strong problem-solving and ownership mindset
• Ability to work in ambiguous and fast-paced environments.
• Strong client/stakeholder management skills.
• Ability to understand business requirements and convert them into technical solutions.
• Strong communication and presentation skills.
• Ability to rapidly learn new technologies and tools.
• Comfortable working with AI-assisted development while maintaining high engineering standards.

Education

• Bachelor's or master’s degree in computer science, Information Technology, Engineering, Data Science, or a related discipline.

Role Summary:

We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and Generative AI/Claude to work closely with clients, business stakeholders, and internal engineering teams. The ideal candidate will combine strong Data Engineering, Software Engineering, Databricks, and Generative AI skills with the ability to understand business problems and rapidly build, deploy, and optimize production-ready solutions. This is a client-facing, hands-on engineering role where you will work from problem discovery and solution design through POC development, production deployment, and ongoing optimization.

Key Responsibilities:

Forward Deployed Engineering

• Work directly with clients and stakeholders to understand business and technical requirements.
• Translate business problems into scalable data, AI, and software solutions.
• Design and develop POCs and rapidly validate technical solutions.
• Convert successful POCs into reliable, production-ready applications.
• Work closely with client engineering and data teams during implementation and deployment.
• Troubleshoot production issues and continuously optimize deployed solutions.
• Act as a technical bridge between clients, delivery teams, data engineers, AI engineers, and architects.

Databricks & Data Engineering

• Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
• Build and optimize data ingestion, transformation, and ETL/ELT pipelines.
• Work with Databricks Lakehouse, Delta Lake, and Unity Catalog.
• Develop Databricks Workflows and production data pipelines.
• Implement data processing solutions for structured and semi-structured datasets.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.

Generative AI & Claude

• Build enterprise AI solutions using Claude and other Large Language Models (LLMs).
• Integrate Claude APIs into applications and business workflows.
• Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data.
• Work with embeddings, vector search, semantic search, and knowledge retrieval.
• Develop AI-powered applications for summarization, classification, information extraction, question answering, and document processing.
• Implement prompt engineering, structured outputs, tool/function calling, and context management.
• Develop and integrate AI agents and multi-step AI workflows where applicable.
• Evaluate LLM responses for accuracy, relevance, groundedness, latency, and cost.
• Implement appropriate AI guardrails, security, and data privacy controls.

Production & Deployment

• Deploy AI and data solutions into production environments.
• Work with APIs, microservices, Git, CI/CD, containers, and cloud platforms.
• Monitor application and pipeline performance and troubleshoot issues.
• Collaborate with Data Scientists and ML Engineers to productionize AI/ML models.
• Ensure solutions meet security, scalability, reliability, and maintainability requirements.

Required Skills & Experience

• 4+ years of experience in Data Engineering, Software Engineering, AI/ML Engineering, or a related field.
• Strong hands-on experience with Databricks.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Delta Lake and Lakehouse Architecture.
• Experience working with Generative AI / LLMs.
• Hands-on experience with Claude / Anthropic APIs is preferred.
• Experience with RAG, embeddings, vector databases, and semantic search.
• Strong understanding of REST APIs and enterprise integrations.
• Experience developing production-grade applications and data pipelines.
• Strong problem-solving and troubleshooting capabilities.
• Excellent communication and client-facing skills.

Preferred Skills

• Experience with Claude Code / Anthropic ecosystem.
• Experience with OpenAI, Azure OpenAI, AWS Bedrock, or other LLM platforms.
• Experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
• Experience with Databricks Unity Catalog, Workflows, and MLflow.
• Experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and CI/CD.
• Exposure to AI agents and agentic workflows.
• Knowledge of AI evaluation, guardrails, security, and responsible AI.
• Experience working in consulting, client delivery, or customer-facing engineering environments.

Key Competencies

• Strong customer-facing and stakeholder management skills.
• Ability to understand ambiguous business problems and translate them into technical solutions.
• Strong ownership and execution mindset.
• Ability to rapidly prototype, iterate, and productionize solutions.
• Strong analytical and troubleshooting skills.
• Comfortable working in fast-paced and dynamic client environments.
• Excellent written and verbal communication.
• Ability to work independently as well as collaboratively with distributed teams.

Strong hands-on experience with Adobe Workfront.

Expertise in Workfront architecture and enterprise implementations.

Advanced knowledge of:

• Workfront configuration
• Custom Forms & Custom Fields
• Workflows & Approval Processes
• Templates
• Reports & Dashboards
• Portfolios & Programs
• User/Role/Security Management

Strong experience with Workfront Fusion.

Experience designing API-based integrations.

Strong knowledge of REST APIs, JSON, HTTP, webhooks, and data mapping.

Experience with enterprise integration platforms/middleware.

Understanding of automation, scalability, security, and governance.

Ability to create high-level and low-level solution designs.

About the company

The client is a quantitative investment firm focused on Indian financial markets. They operate a multi-strategy, multi-manager platform designed to generate consistent, risk- adjusted returns.

Their approach combines systematic investment methods, rigorous quantitative research and institutional-grade manager evaluation. We bring together research, technology and data to build scalable investment solutions.

Role Overview

We are seeking a Quantitative Developer with strong C++ and Python expertise to convert mathematical models and research prototypes into reliable, high-performance analytical engines.

You will work closely with Quantitative Research, Data Engineering, AI and Product Engineering teams throughout the full model lifecycle—from research handover and production implementation to validation, deployment and ongoing support.

This role is ideal for someone who enjoys working at the intersection of quantitative finance, numerical computing and production software engineering.

Key Responsibilities

Research Production

• Translate mathematical models and Python research prototypes into robust, production-quality C++.
• Develop reusable components for risk analytics, forecasting, portfolio analysis and simulation.
• Build efficient Python interfaces for C++ components using pybind11 or similar technologies.
• Ensure production implementations remain mathematically and numerically consistent with the underlying research.
• Establish clear and reproducible processes for transitioning models from research to production.

Engine Development and Validation

• Design and develop analytical engines capable of processing historical, batch and streaming data.
• Integrate calculation components with data pipelines, APIs, databases and downstream applications.
• Validate production implementations against research prototypes, benchmark datasets and expected results.
• Develop automated numerical, unit, integration, regression and performance tests.
• Identify and resolve numerical stability, precision and edge-case issues.
• Optimize calculation speed, memory usage, concurrency and scalability.
• Profile and benchmark critical components to meet defined performance requirements.

Deployment and Delivery

• Package analytical engines as libraries, services, APIs or containers.
• Support deployment across internal infrastructure and client-controlled environments.
• Configure engines for different datasets, workflows and institutional requirements.
• Assist with integration testing, production upgrades, issue diagnosis and technical troubleshooting.
• Implement appropriate logging, monitoring and error-handling capabilities.
• Document interfaces, assumptions, configurations, dependencies and deployment requirements.

Collaboration and Ownership

• Work closely with Quantitative Research, Data Engineering, AI and Product Engineering teams.
• Participate in technical design discussions, code reviews and quantitative model reviews.
• Communicate implementation trade-offs, constraints and risks clearly to technical and quantitative stakeholders.
• Take end-to-end ownership of assigned components, from research handover through production deployment and support.
• Contribute to engineering standards, reusable libraries and development best practices.

Required Qualifications

• Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, Quantitative Finance or a related discipline.
• Strong professional programming experience in modern C++, including object- oriented and generic programming.
• Proficiency in Python and scientific-computing libraries such as NumPy, pandas or SciPy.
• Experience translating mathematical or analytical prototypes into production software.
• Strong understanding of algorithms, data structures, software architecture and design principles.
• Experience building automated unit, integration and performance tests.
• Familiarity with numerical methods, floating-point behaviour and numerical validation.
• Experience profiling and optimizing compute-intensive or data-intensive applications.
• Proficiency with Git and modern software-development practices.
• Strong analytical, debugging and problem-solving skills.
• •Ability to work effectively with both researchers and software engineers.

Preferred Qualifications

• Experience with pybind11, Boost.Python, Cython or similar interoperability technologies.
• Knowledge of quantitative finance, portfolio analytics, risk modelling, forecasting or simulation.
• Familiarity with time-series data and financial-market datasets.
• Experience developing applications that process batch or real-time streaming data.
• Exposure to concurrent, parallel or distributed computing.
• Experience with containerization and deployment technologies such as Docker.
• Familiarity with Linux environments, CI/CD pipelines and cloud or on-premises infrastructure.
• Experience building analytical libraries, calculation services or APIs for institutional users.
• Knowledge of Indian financial markets is advantageous

JD:

We are looking for a skilled Axiom Technical Analyst / Developer to support and enhance regulatory reporting platforms.

The ideal candidate will have strong hands-on experience with Axiom, solid SQL skills, and a good understanding of ETL processes. Exposure to Python is a plus.

This role involves close collaboration with Finance, and Data Engineering teams to ensure accurate, timely, and compliant data reporting.

ROLE:  

Address technical issues relating to software implementation, function, and upgrades. Resolve customer complaints or problems and create product problem reports and troubleshoot documents for each issue. Work closely with application support and development teams to identify and resolve any technical problems that might arise during the development of software. Work with Implementation teams and Account managers to recommend solutions to new customer implementations and workflows.  

ESSENTIAL DUTIES and RESPONSIBILITIES: 

• Understanding the PeopleScout architecture and framework  
• Provide L2 support for tickets passed on by L1 support team using advanced knowledge of Java, SQL, Stored Procedures, Functions, and database development.  
• Analyze and understand Java code to debug, trace, and communicate technical issues effectively with the Development team.  
• Review application logs, perform exception analysis, monitor system performance, and identify root causes to ensure timely issue resolution and optimal application performance.
• Provide technical support to application support team
• Develop solutions to complex customer and software problems
• Assist with software design and development  
• Work within an agile environment  
• Deliver sprint commitments on time
• Be responsible for your own code, and work with others to improve the quality and deliver of theirs  
• Document troubleshooting guides and outcomes of problems, analysis and solutions for future re-use  

MUST HAVE SKILLS: 

• 5 to 8 years of experience in L2 Application Support, preferably supporting SaaS products.
• Strong troubleshooting skills with Java applications, SQL, and REST APIs.  
• Strong hands-on experience with Core Java (Java 8 or above).  
• Good understanding of Spring Boot and Java-based enterprise applications.
• Experience troubleshooting production issues, performing root cause analysis (RCA), and resolving incidents within SLA  
• Strong SQL skills with databases such as Oracle, MySQL, PostgreSQL, or SQL Server.  
• Experience working with REST APIs, JSON, and API testing tools like Postman.
• Ability to analyze application logs using tools such as Splunk, Kibana, ELK, or Grafana.
• Excellent customer communication skills with experience managing client interactions and providing timely updates.
• Familiarity with ServiceNow/Jira, Linux basics, and log analysis for application support

Role Overview

We are looking for experienced Azure Databricks Data Engineers with strong hands-on expertise in Apache Spark/PySpark, Python, SQL, and Azure Data Factory (ADF). The candidate will be responsible for designing, developing, and optimizing scalable data engineering solutions on the Azure cloud platform.

Mandatory Skills

• Strong hands-on experience with Azure Databricks
• Strong knowledge of Apache Spark and/or PySpark
• Proficiency in Python
• Strong SQL development and query optimization skills
• Hands-on experience with Azure Data Factory (ADF)
• Experience developing and maintaining scalable ETL/ELT data pipelines
• Good understanding of Azure data engineering concepts and cloud-based data platforms

Key Responsibilities

• Design, develop, and maintain data pipelines using Azure Databricks and ADF
• Develop efficient data processing solutions using PySpark/Spark and Python
• Write complex SQL queries for data transformation, validation, and analysis
• Build scalable ETL/ELT workflows for large datasets
• Optimize Spark jobs, Databricks notebooks, and data pipelines for performance
• Integrate data from multiple sources into Azure-based data platforms
• Implement data quality, validation, error handling, and monitoring mechanisms
• Troubleshoot production issues and provide timely resolutions
• Collaborate with data architects, analysts, developers, and business stakeholders
• Follow best practices for code quality, security, performance, and maintainability

Experience Requirements

For 5+ Years

• 5+ years of overall experience in data engineering
• Strong hands-on experience in Azure Databricks, PySpark/Spark, Python, SQL, and ADF
• Experience working on enterprise-scale data pipelines

For 9+ Years

• 9+ years of overall experience in data engineering
• Strong expertise in Azure Databricks and modern Azure data engineering
• Proven experience designing and optimizing large-scale data pipelines
• Ability to lead technical discussions and mentor junior engineers

Preferred Skills

• Azure Data Lake Storage (ADLS)
• Delta Lake
• Databricks Workflows
• Azure DevOps / CI-CD
• Git
• Data warehousing concepts
• Experience with Agile/Scrum methodologies

Data Engineer - Power BI Modelling

Level: Senior to Advanced - 5-15 years

Locations: Mumbai / Bengaluru

Joining an existing data engineering squad, you own Power BI semantic modeling on top of PySpark/SQL pipeline engineering, delivering enterprise-grade reporting and analytics. As an embedded Data Engineer, you turn PySpark pipelines into trusted Power BI models for the business.

Note: Shares a common PySpark/Snowflake base with "Data Engineer - Graphing" - source together, differentiate on semantic-modeling vs. graphing depth at interview.

Key responsibilities

1. Model semantically. Build and maintain Power BI semantic models (DAX, star schemas) for enterprise reporting.
2. Build pipelines. Develop PySpark/Python and SQL pipelines feeding the Snowflake environment.
3. Partner with stakeholders. Translate reporting requirements into performant data models.
4. Ensure data quality. Validate accuracy and performance of models and underlying pipelines.
5. Collaborate. Operate inside the existing squad with no separate delivery lead required.
6. Explore GenAI. Apply GenAI techniques to reporting and data use cases as opportunities arise.

Must-have qualifications

• Python and PySpark
• SQL
• Power BI semantic modeling (DAX, data modeling)

Preferred

• Snowflake; Dataiku
• GenAI exposure

What success looks like – first 6 to 12 Months

• Power BI models adopted for key reporting use cases
• Reliable PySpark/SQL pipelines feeding those models
• Smooth integration into the existing squad

Confidential – Wissen Technology

About MyOperator

MyOperator is a Business AI Operator platform that brings together WhatsApp, Calls, and AI-powered chat & voice bots to help businesses manage customer operations such as Sales, Support, Escalations, Feedback, and Refunds. With 12,000+ businesses using our platform, we operate at meaningful scale and power mission-critical communication workflows.

About the Role

We are looking for a Senior QA Engineer (SDET) to own and scale automation across our web, backend, mobile, and AI-driven workflows.

This is a hands-on automation engineering role, not a manual testing role. You will build and maintain Playwright-based automation, strengthen mobile and API testing, integrate automation into CI/CD, and work closely with engineering teams to catch issues before they reach production.

What You'll Do

• Design, build, and maintain Playwright-based end-to-end automation for web applications.
• Build and maintain mobile test automation for Android and/or iOS using Appium, Espresso, XCUITest, or equivalent tools.
• Develop automated tests for REST/GraphQL APIs and validate backend data using SQL.
• Integrate automated test suites into CI/CD pipelines and maintain reliable test execution.
• Identify and resolve flaky tests and continuously improve automation coverage and reliability.
• Use AI coding assistants such as Claude, GitHub Copilot, Cursor, or similar tools for test authoring, debugging, and test-data generation.
• Work closely with frontend, backend, and AI engineering teams to identify testability gaps early.
• Contribute to testing AI/LLM-driven features, where expected outputs may not always be deterministic.

Must Have

• 6–8 years of experience in QA/SDET or test automation roles.
• Strong hands-on experience with Playwright — mandatory.
• Hands-on mobile automation experience — mandatory using Appium, Espresso, XCUITest, or equivalent.
• Strong experience in API/backend automation using REST or GraphQL.
• Good knowledge of SQL for database validation.
• Strong programming and automation skills.
• Experience integrating automation into CI/CD pipelines.
• Practical experience using AI coding assistants such as Claude, GitHub Copilot, Cursor, or similar.
• Ability to independently own automation initiatives.

Good to Have

• Experience testing AI/LLM, chatbot, conversational AI, or voice bot products.
• Experience with Langfuse or similar LLM observability tools.
• Experience with Datadog or similar APM tools.
• Experience with GitHub Actions, Jenkins, or similar CI/CD tools.
• Exposure to performance/load testing tools such as k6 or JMeter.

This Role Is Not For

• Candidates whose experience is primarily in manual testing.
• Candidates with limited hands-on coding or automation experience.
• Candidates without practical Playwright experience.
• Candidates without mobile automation experience.
• Candidates who have only executed test cases on an existing framework without meaningful automation ownership.

Why MyOperator?

Work on an AI-first customer operations platform used by 12,000+ businesses, and build automation across web, backend, mobile, and AI workflows while working closely with engineering teams.

If you enjoy writing automation code, solving complex testing problems, and taking end-to-end ownership, we'd love to hear from you.

Greetings From NAM Info Pvt Ltd

Job Title: STIBO STEP / Master Data Management Consultant

Experience: 6–8 Years

Job Summary

We are looking for an experienced STIBO STEP / Master Data Management (MDM) Consultant with strong hands-on experience in STIBO STEP 11.x. The candidate should be capable of designing and configuring MDM solutions, developing integrations, managing data quality, and working directly with customer stakeholders.

Key Responsibilities

• Understand business requirements and translate them into STIBO STEP configurations and technical solutions.
• Design and configure data models, attributes, hierarchies, classifications, relationships, and workflows.
• Configure business validation rules, lifecycle states, roles, permissions, and STEP UI components.
• Develop and manage imports, exports, publications, and syndications.
• Build integrations between STIBO STEP and systems such as SAP, Oracle ERP, eCommerce, PLM, and DAM.
• Work with REST/SOAP APIs, file-based interfaces, ETL tools, and message queues.
• Implement data quality, data governance, stewardship, match/merge, and reference data management processes.
• Troubleshoot performance and integration issues and perform root cause analysis.
• Support environment promotion, configuration transport, versioning, CI/CD, and deployment activities.
• Prepare technical/functional documentation, release notes, and training materials.
• Conduct customer workshops, present solutions, and communicate project status, risks, and issues.

Required Skills

• 6–8 years of experience in STIBO Master Data Management (MDM).
• Strong hands-on experience with STIBO STEP 11.x.
• Good knowledge of STEP data modeling, workflows, business rules, imports/exports, publications, and syndication.
• Programming/scripting knowledge in Java or JVM-based technologies.
• Strong knowledge of SQL, XML, XSD, XPath, and XSLT.
• Experience with REST and SOAP APIs.
• Experience integrating STIBO with enterprise systems such as SAP, Oracle ERP, eCommerce, PLM, or DAM.
• Strong experience with Oracle, MS SQL, or PostgreSQL.
• Good understanding of data quality and MDM governance.
• Strong communication and customer-facing skills.

Good to Have

• Experience with Informatica, Talend, or similar ETL tools.
• Knowledge of message queues and event-driven integrations.
• Experience with CI/CD and DevOps practices.
• Experience in performance optimization, security, and audit compliance.
• Ability to work independently and drive tasks to completion.

About MyOperator

MyOperator is a Business AI Operator platform that brings together WhatsApp, Calls, and AI-powered chat & voice bots to help businesses manage customer operations such as Sales, Support, Escalations, Feedback, and Refunds. With 12,000+ businesses using our platform, we operate at meaningful scale and power mission-critical communication workflows.

About the Role

We are looking for a Senior QA Engineer (SDET) to own and scale automation across our web, backend, mobile, and AI-driven workflows.

This is a hands-on automation engineering role, not a manual testing role. You will build and maintain Playwright-based automation, strengthen mobile and API testing, integrate automation into CI/CD, and work closely with engineering teams to catch issues before they reach production.

What You'll Do

• Design, build, and maintain Playwright-based end-to-end automation for web applications.
• Build and maintain mobile test automation for Android and/or iOS using Appium, Espresso, XCUITest, or equivalent tools.
• Develop automated tests for REST/GraphQL APIs and validate backend data using SQL.
• Integrate automated test suites into CI/CD pipelines and maintain reliable test execution.
• Identify and resolve flaky tests and continuously improve automation coverage and reliability.
• Use AI coding assistants such as Claude, GitHub Copilot, Cursor, or similar tools for test authoring, debugging, and test-data generation.
• Work closely with frontend, backend, and AI engineering teams to identify testability gaps early.
• Contribute to testing AI/LLM-driven features, where expected outputs may not always be deterministic.

Must Have

• 6–8 years of experience in QA/SDET or test automation roles.
• Strong hands-on experience with Playwright — mandatory.
• Hands-on mobile automation experience — mandatory using Appium, Espresso, XCUITest, or equivalent.
• Strong experience in API/backend automation using REST or GraphQL.
• Good knowledge of SQL for database validation.
• Strong programming and automation skills.
• Experience integrating automation into CI/CD pipelines.
• Practical experience using AI coding assistants such as Claude, GitHub Copilot, Cursor, or similar.
• Ability to independently own automation initiatives.

Good to Have

• Experience testing AI/LLM, chatbot, conversational AI, or voice bot products.
• Experience with Langfuse or similar LLM observability tools.
• Experience with Datadog or similar APM tools.
• Experience with GitHub Actions, Jenkins, or similar CI/CD tools.
• Exposure to performance/load testing tools such as k6 or JMeter.

This Role Is Not For

• Candidates whose experience is primarily in manual testing.
• Candidates with limited hands-on coding or automation experience.
• Candidates without practical Playwright experience.
• Candidates without mobile automation experience.
• Candidates who have only executed test cases on an existing framework without meaningful automation ownership.

Why MyOperator?

Work on an AI-first customer operations platform used by 12,000+ businesses, and build automation across web, backend, mobile, and AI workflows while working closely with engineering teams.

If you enjoy writing automation code, solving complex testing problems, and taking end-to-end ownership, we'd love to hear from you.

About the Role

We are looking for a motivated Data Engineer with 2+ years of professional experience to join our team. You will be responsible for designing, developing, and maintaining scalable data pipelines and cloud-based data solutions while taking ownership across the full software development lifecycle.

The ideal candidate will have strong experience in modern data engineering practices, cloud platforms, and marketing/advertising data integrations such as Google Ads, Meta Ads, and analytics platforms.

This role is suited for someone who enjoys solving complex data challenges, building reliable systems, and working in a fast-paced environment.

Key Responsibilities

• Design, build, and maintain scalable and reliable ETL/ELT data pipelines.
• Develop and optimize data models, transformations, and warehouse solutions for analytics and reporting.
• Work with marketing and advertising datasets from platforms such as Google Ads, Meta Ads, Google Analytics, and similar ecosystems.
• Integrate APIs, third-party systems, and cloud-native services into data workflows.
• Optimize complex SQL queries and improve pipeline performance and reliability.
• Implement data quality checks, monitoring, and observability across pipelines.
• Collaborate with cross-functional teams including product, analytics, and engineering teams to deliver data-driven solutions.
• Contribute to software engineering best practices including Git workflows, CI/CD pipelines, testing, and documentation.
• Participate in architecture discussions and help improve data platform standards and best practices.
• Build and maintain solutions within Google Cloud Platform (GCP) environments.

Qualifications

• 2+ years of professional experience in Data Engineering or related fields.
• Strong proficiency in Python programming.
• Advanced SQL skills with experience in query optimization and data warehousing concepts.
• Experience working with marketing and advertising platforms such as Google Ads, Meta Ads, Google Analytics, DV360, or similar platforms.
• Experience working with AI-assisted coding and development tools such as Claude Code, Cursor, or similar platforms
• Hands-on experience leveraging AI-based development tools to accelerate data engineering implementation and automation
• Familiarity with AI-powered coding assistants and agentic development workflows
• Understanding of marketing data pipelines, attribution reporting, campaign analytics, or customer analytics is highly desirable.
• Hands-on experience with at least one major data engineering technology such as Airflow, Spark, Kafka, Databricks, or similar frameworks.
• Strong experience with Google Cloud Platform (GCP) services such as BigQuery, Cloud Run, Cloud Functions, GCS, or Composer.
• Familiarity with APIs, Linux environments, CLI tools, Git, and CI/CD workflows.
• Strong understanding of data pipeline design, orchestration, monitoring, and troubleshooting.
• Excellent communication, collaboration, and problem-solving skills.
• Ability to work independently and contribute across multiple technical domains.

Who are we?

Inflexion Analytics is a team of data science and analytics consultants based in London, UK, and Bangalore India. Founded in 2015, we have built a strong track record and foundation serving demanding clients. We are now looking to achieve significant growth and become a leading specialist consultancy in the data science field.

What we do?

We help businesses to improve performance through better insight and decision-making. To achieve this, we offer services across the data science value chain including; data strategy, data engineering, data insights, and visual analytics. We work with a global client base, including clients based in the US, UK, Europe, and Australia. 

ElaraRise Technologies is hiring a Senior Backend / Cloud Engineer.

You'd be the first backend hire on a founding team of five, building a transaction-anchored POS and Vision AI platform for retail and food-service operators in India and East Africa.

What you'd own: the POS backend, the transaction cache, real-time updates over SignalR, and the one-way ERP export interface. Offline-first by design — sites lose connectivity regularly, and the system has to keep selling and reconcile cleanly when the line returns.

We're looking for:

✅ 5+ years hands-on .NET — real depth, no shortcuts

✅ 2+ multi-tenant SaaS projects delivered end to end

✅ Azure (IoT / cloud) experience

✅ SaaS architecture mindset

Stack: .NET 10 · C# · Blazor · Azure · ABP Commercial

ABP experience isn't required. We provide the licence, paid support and ramp-up time — we hire for fundamentals.

📍 Nellore, Andhra Pradesh

📅 Start: October 2026

Senior pay for senior skill.

#DotNet #Azure #BackendEngineer #SaaS #Nellore #AndhraPradesh

Design, develop, and maintain ETL pipelines involving large-scale data.

Develop data processing and analytics applications primarily using PySpark and Python.

Build scalable and distributed data processing solutions using Apache Spark.

Develop and deploy data applications on AWS cloud.

Work with AWS services related to storage, compute, ETL, data warehousing, analytics, and streaming.

Implement distributed storage and processing solutions capable of handling high-volume datasets.

Design data processing applications with a focus on performance, scalability, reliability, and optimization.

Work with both SQL and NoSQL databases for data storage, processing, and analytics.

Write, optimize, and analyze SQL, HQL, and NoSQL queries.

Troubleshoot data pipeline and processing issues and ensure data quality and reliability.

Collaborate with data engineers, analysts, architects, and other technical teams to deliver data-driven solutions.

What role will you play? 

As a Full Stack Engineer, you will play a pivotal role in our development team, bridging the gap between the visual elements and the server-side infrastructure. You will be instrumental in developing full-fledged, scalable applications by combining the art of design with the science of programming. With your expertise in both front-end and back-end technologies, you will ensure the entire stack is designed and built for speed and functionality.  

Your day to day will involve designing and developing dynamic, high-quality web applications, leveraging the Node.js and python for the back end services and React/Angular for the front end. Close collaboration with UI/UX designers will be essential, allowing you to bring web designs to life while ensuring high performance and responsiveness. Additionally, you will actively participate in coding, debugging, and testing to deliver reliable solutions whilst also working closely with other developers, designers, and product managers, fostering a collaborative environment to meet project goals and deadlines effectively. 

What you offer 

• Proficiency in Typescript and a good understanding of React  
• Solid experience with the Node.js, including the ability to develop RESTful APIs 
• Experience with containerisation of service using Docker 
• Knowledge of modern authorisation mechanisms, such as JSON Web Token (JWT)  
• Familiarity with SQL databases, such as PostgreSQL 
• Experience with Kafka or other event driven tools and tech 
• Nice to have some experience integrating with LLMs through open AI, Gemini etc. 
• Nice to have exposure to AI tooling – Claude, Copilot, Cursor etc. 
• AWS experience is a nice to have 

Role Summary

Seeking an experienced SQL Developer with strong expertise in Data Lake architecture, Data Engineering, AI/ML data modelling, and Vector Database design. The candidate will be responsible for building scalable data platforms, developing optimized SQL solutions, designing AI-ready data models, and supporting enterprise analytics and GenAI initiatives.

Key Responsibilities

• Design, develop, and optimize complex SQL queries, stored procedures, views, and database objects.
• Build, maintain, and govern enterprise Data Lakes for structured, semi-structured, and unstructured data.
• Design scalable data models for Analytics, Machine Learning (ML), and AI applications.
• Develop and maintain data ingestion, transformation, and data preparation pipelines.
• Architect and manage Vector Database solutions supporting GenAI, semantic search, embeddings, and RAG-based applications.
• Ensure data quality, security, performance, governance, and scalability across platforms.
• Integrate data from multiple enterprise systems, databases, APIs, and business applications.
• Collaborate with Business, Analytics, Data Science, and AI teams to deliver enterprise data solutions.

Mandatory Skills

• Advanced SQL Development (SQL Server, PostgreSQL, Oracle, MySQL, etc.)
• Data Lake Architecture, Development, and Maintenance
• Data Warehousing & Dimensional Data Modelling
• AI/ML Data Modelling and Feature Engineering
• Python for Data Engineering, Data Processing, and Automation
• Query Performance Tuning & Database Optimization
• Data Governance & Data Quality Management
• Vector Database Architecture and Management (Pinecone, Qdrant, Weaviate, Milvus, Chroma, or similar)
• Experience handling large-scale structured and unstructured datasets

Preferred Skills

• Experience with GenAI, RAG (Retrieval-Augmented Generation), Embeddings, and LLM-based applications
• PySpark and Distributed Data Processing
• Power BI or Enterprise Reporting Platforms
• Knowledge of MLOps, AI data pipelines, and modern data architectures

Key Attributes

• Strong analytical and problem-solving skills
• Ability to independently own end-to-end data platform solutions
• Excellent communication and stakeholder management skills
• Passion for Data Engineering, AI, ML, and GenAI technologies

Ideal Candidate

A hands-on SQL Developer who can build and maintain enterprise Data Lakes, design AI/ML-ready data models, develop Python-based data solutions, and architect Vector Database platforms to support advanced analytics, AI, and GenAI initiatives.

Job Title: Automation Engineer – Watermelon Tool 

Experience: 6–7 Years

Location: Bangalore

Work Mode: Hybrid

Notice Period: Immediate Joiners (Apply only if you can join within 15 Days)

Key Responsibilities:

Design, develop, and maintain automated test scripts using the Watermelon automation tool.

Build and enhance automation frameworks for web, API, and enterprise applications.

Analyze business and functional requirements to identify automation opportunities.

Execute automated regression, smoke, sanity, and functional test suites.

Maintain reusable automation components and improve test coverage.

Integrate automation scripts with CI/CD pipelines.

Perform root cause analysis for failed test cases and provide detailed defect reports.

Work closely with developers, business analysts, and QA teams to resolve issues.

Ensure automation standards, coding best practices, and documentation are followed.

Participate in Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.

Required Skills:

5–10 years of experience in Automation Testing.

Strong hands-on experience with the Watermelon automation tool (mandatory).

Experience in test automation framework development and maintenance.

Knowledge of API testing and automation.

Experience with SQL for database validation.

Familiarity with Git or other version control systems.

Experience with CI/CD tools such as Jenkins, Azure DevOps, or GitLab CI.

Strong understanding of SDLC, STLC, and Agile methodologies.

Excellent debugging, analytical, and problem-solving skills.

Good verbal and written communication skills.

Preferred Skills:

Experience with Selenium, Playwright, Cypress, or similar automation tools.

Knowledge of Java, Python, or JavaScript for automation scripting.

Exposure to cloud platforms such as AWS, Azure, or GCP.

Experience working in enterprise-scale automation projects.

ISTQB or equivalent testing certification is an added advantage.

Roles & Responsibilities:

Develop scalable and maintainable automation solutions.

Improve automation coverage and reduce manual testing effort.

Collaborate with stakeholders to deliver quality software releases.

Identify automation improvements and implement best practices.

Support production validation and release testing activities.

Mandatory Skills:

Watermelon Automation Tool

Test Automation

Automation Framework Development

API Testing

SQL

Git

CI/CD

Agile Methodology

Generative AI Engineer 

Role Overview:

You will be responsible for the hands-on development, coding, and deployment of AI-powered features. Your focus is on writing clean, efficient code to integrate LLMs into our existing tech stack, building robust data pipelines for RAG, and ensuring the reliability of model outputs through rigorous testing and optimization.

Key Responsibilities

• Application Implementation: Code and integrate LLM APIs (OpenAI, Anthropic, etc.) or local models into backend services using Python, FastAPI, etc.,
• MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript) to expose internal databases, APIs, and file systems to AI agents.
• RAG Implementation: Build and maintain the "plumbing" for Retrieval-Augmented Generation—specifically coding the data ingestion scripts, text chunking logic, and metadata filtering.
• Vector DB Management: Perform day-to-day operations on vector databases (Pinecone, Milvus, etc.), including indexing, querying, and optimizing search retrieval.
• Prompt Programming: Develop, version-control, and refine complex prompt templates (using Jinja2 or similar) to ensure consistent structured outputs (JSON/YAML).
• Agent Development: Implement multi-step workflows using LangChain, LangGraph, CrewAI etc.,, focusing on tool-calling logic and error handling.
• Evaluation & Testing: Build automated test suites to detect "hallucinations" and measure accuracy using frameworks.
• Performance Tuning: Implement caching layers and streaming responses to reduce latency and improve the end-user experience; Token optimization.
• Data Pre-processing: Clean and tokenize datasets for model fine-tuning or high-quality context retrieval.

Technical Skills (The "Execution" Stack)

• Language: Advanced Python (Asyncio, Pydantic) and optional TypeScript/Node.js (for full-stack integration).
• AI Frameworks: Hands-on experience with any of LangChain, LlamaIndex, and Hugging Face Transformers. RAG and Vector search concepts.
• Data Handling: Proficiency in SQL and handling unstructured data formats (PDFs, Markdown, JSON).
• Deployment: Practical experience with Docker, GitHub Actions (CI/CD), and experience with OpenTelemetry, LangSmith, Weights & Biases etc., Understanding of evaluation/guardrails.
• MCP/API Proficiency: Deep understanding of RESTful APIs, Streaming HTTP, MCP server vs client, JSONRPC

Position: Senior Professional Services Engineer - NTRX

Location: Pune, Hinjewadi PH-2

Experience: 5-7 Years

Budget: 11-12 LPA

Work Type: Hybrid | 2 Days WFO

Role Summary

The NTR-x PSE will own installation, integration & support of NiCE NTR-x recording solutions for clients in Financial Services/Banking domain.

Must Have

 - Domain: 5-7 Yrs experience in Financial Services / Banking domain

 - Recording Solutions: Hands-on with NiCE / Verint / any other recording solutions - Installation, Configuration, Upgrades & Maintenance on Windows/Cloud & NTRX

 - OS: Strong Microsoft Windows Server/OS knowledge

 - Telephony: IP/SIP communication analysis + Strong telephony background

 - Networking: OSI 7-layer, TCP, UDP, LAN/WAN, NICs, Switches, Routers

 - Troubleshooting: Wireshark, Log Analysis, Network testing utilities

 - Scripting: Basic SQL / Shell - Query & Update knowledge

 - Client Skills: Strong customer-facing skills. Able to lead tech discussions & represent NiCE in client meetings

Good to Have

 - Integrations: Experience with PBX, Switch, ACD - Avaya, Cisco, Microsoft Teams, Amazon Connect

 - Cloud: AWS - Primary, Azure. Virtualization - VMware, Citrix

 - Advanced: MDC, LDAP, SSO, ACD Integration, DB Migration, DR & HA Designs

 - Security: Active Directory, GPO, DNS, Certificate Authority, EFS, Hardening

Added Advantage

 - Certifications: MCP / MCSE, CCNA, VMware, Citrix, AWS, Azure

 - Database: Microsoft SQL Server 2012+ - Install, Config, Admin, Backup, Recovery

Key Responsibilities

 - Install, integrate & configure NiCE NTR-x recording solution remotely as per standards

 - Develop/configure software features per design specs & customer requirements

 - Plan & execute Unit, Functional & System testing. Support UAT & Data Validation

 - Assist customers/vendors with NiCE integration points

 - Provide technical expertise across NiCE product suite - Design, Support, QA

 - Escalate issues to Support, R&D & Management when needed

 - Proactive communication with client & management on progress & risks

 - Support after-hours, weekends, client-site & cross-time-zone as required

 - Share customer feedback to R&D for product enhancements.

RPA.

Must Have:

• More than 8 years of overall experience in Robotic Process Automation and ML technologies. 

• 4-5 years of direct experience in developing with UiPath/Automation Anywhere (A360), Python

• Strong Knowledge in SQL to write queries (Insert, Delete, Select , Update & Joins) and have knowledge on Stored Procedure to Execute or Modify.

• Experience on Custom / Build in Queues like Workload Management Queues.

• Certifications with other RPA software tools (e.g., Automation Anywhere, UiPath etc.) preferred

Nice to Have Skills:

Experience with business process improvement, including process mapping and design-based thinking preferred

Bachelor’s degree in computer science experience.

Design, develop, test, and optimize solutions to automate processes using automation technology including AA/UiPath.

Designs automated solutions in accordance with enterprise leading practices and design principles.

Assists in the collection and documentation of solution design requirements.

Builds and test automation processes including unit and integration testing.

Analyzes and resolves automation software issues where required.

Participates in peer review of solution designs

TECHNICAL SKILLS:

Automation Tools : UiPath, Automation Anywhere A360

Reporting Tools : SAP BO 4.2, Tableau

Databases : MS SQL Server 2010/2008, Teradata, Stored Procedures

Languages : .Net, XML, VB Scripting, Python

Platforms : Unix, Windows 10/7/XP

SDLC Methodology : Agile, Waterfall

Other Tools : MS Office, XML Editor, Jira, SharePoint, ALM, Service Now, Rally, Visual studio

About the Programme 

Developing an enterprise AI platform focused on financial compliance and intelligence.  

Role Overview 

We are looking for a strong Data Engineer to own the data foundation of the platform. Every model, every AI output, and every compliance decision the system makes depends on data arriving reliably, completely, and on time. You will design and build the ingestion pipelines from all source systems into the data platform, own the pipeline monitoring infrastructure, and work closely with internal IT and operations teams to extract data from complex enterprise source 

systems.  

Key Responsibilities 

Data Discovery & Audit 

• Conduct a thorough data audit with internal IT and operations teams — map every data 

source needed for the platform, assess what already exists on the data platform, and identify gaps. 

• Document data sources, schemas, update frequencies, and quality issues for all relevant datasets  

• Raise data gaps and quality risks to the Solutions Architect  

Pipeline Design & Build 

• Design and build ingestion pipelines from all source systems — ERP, government portals, supplier portals, and banking feeds — into the data platform. 

• Design pipelines for both batch and real-time ingestion patterns 

• Ensure pipelines are idempotent, resumable, and handle source system failures gracefully without data loss or duplication. 

Data Quality & Reliability 

• Build pipeline monitoring and alerting so data failures are caught and flagged before they corrupt model training or inference. 

• Define and implement data quality checks at the point of ingestion — schema validation, completeness checks, and anomaly detection on incoming data volumes. 

• Maintain clear data lineage so the team always knows where a data point came from and when it was last updated. 

Collaboration & Handoff 

• Work closely with internal IT and automation team who hold institutional knowledge of the source systems — this is not a solo exercise. 

• Hand off clean, well-documented datasets to the ML Engineers and LLM Engineer for model training and knowledge base building. 

• Support the MLOps Engineer in ensuring production pipelines are stable and monitored post-deployment. 

Required Qualifications 

Education 

•B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field. 

Experience 

• 5+ years of data engineering experience with at least 2 years working on production pipelines at enterprise scale. 

• Demonstrated experience building pipelines from complex enterprise source systems — ERP or equivalent. 

• Experience building both batch and real-time / streaming ingestion pipelines. 

Technical Skills 

• Languages: Python and PySpark; SQL proficiency essential. 

• Data Platform: Databricks and Delta Lake — must have hands-on production experience. 

• Pipeline Orchestration: Apache Airflow, Databricks Workflows, or equivalent. 

• Streaming: Kafka, Spark Structured Streaming, or equivalent for real-time ingestion patterns. 

• ERP Integration: Experience extracting data from SAP or equivalent large ERP systems strongly preferred. 

• API Integration: REST API consumption for government portal or third-party data feeds. 

• Data Quality: Experience with data quality frameworks — Great Expectations or equivalent. 

• Observability: Pipeline monitoring, alerting, and data lineage tooling. 

Preferred Qualifications 

• Familiarity with SAP data models  

• Prior experience with government API ecosystems — GSTN, ICEGATE, or similar. 

• Experience building pipelines that feed ML model training workflows. 

• Exposure to Unity Catalog or similar data catalogue and governance tools. 

• Prior work in fintech, compliance, or tax technology environments. 

Job Title: Senior Data Tester

Location : Hyderabad

Mode: Hybrid

Notice Period: Immediate Joiner

Key Responsibilities:

• 8+ years of experience in ETL/data testing.
• Design, implement, and execute data validation test plans and test cases.
• Understanding of data modelling and data governance principles.
• Experience with test automation frameworks and scripting (e.g., Python, Shell)Conduct thorough ETL testing, including data extraction, transformation, and loading.
• Validate data integrity across various sources and destinations (data lakes, warehouses, etc.)
• Perform data reconciliation and analysis to identify inconsistencies or data quality issues.
• Develop and maintain automated data testing frameworks using SQL or scripting languages.
• Strong experience with SQL and writing complex queries for data validation.
• Knowledge of data warehouse concepts and testing tools. Experience with ETL tools (e.g., Informatica, Talend, SSIS, etc.)
• Familiarity with cloud platforms (Azure, GCP) and modern data tools (e.g., Snowflake, Big Query).
• GCP is mandatory. Experience in Agile development and working within cross-functional teams.
• Exposure to BI tools (Power BI, Tableau, Looker)
• Familiarity with CI/CD pipelines and version control systems like Git ISTQB or equivalent testing certifications.

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
• Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
• Work with cloud platforms GCP, Azure to manage data infrastructure.
• GCP as mandatory skills
• Collaborate with analytics and product teams to understand data needs and deliver solutions.
• Ensure data quality, reliability, security, and compliance across all data systems.
• Mentor junior data engineers and contribute to best practices and code reviews.
• Monitor and troubleshoot data pipeline performance and resolve data-related issues.
• Automate data validation, monitoring, and alerting processes.
• 8+ years of experience in data engineering or software engineering with a data focus.
• Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
• Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of data modeling, data lakes, and ETL/ELT design.
• Hands-on experience with orchestration tools like Airflow, dbt, or similar.
• Solid experience with cloud data platforms (AWS/GCP/Azure).
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
• Experience working in a DevOps or DataOps environment.
• Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
• Experience supporting machine learning workflows and data science initiatives.

Job Description:

Position: Senior Data Engineer

Location: Chennai / Pune / Bangalore / Hyderabad

Working Type: WFO

Shift: UK Shift (2:00 – 11:00 PM)

Experience : 7+ years overall

Interviews: Assessment || 2 Interview rounds.

Notice Period: Immediate Joiner

Key Responsibilities

Implement ingestion, transformation, and optimization of enterprise data sources into Microsoft Fabric Lakehouse environments.

Configure and optimize Fivetran connectors (Oracle, SQL DB, etc.)

Manage large-volume ingestion and backfill operations

Implement Bronze to Silver transformation pipelines

Develop incremental load and CDC logic

Optimize Lakehouse performance and storage patterns

Implement monitoring (record counts, load duration, failure tracking)

Support Dev/Test/Prod promotion processes

Required Qualifications

7+ years of data engineering experience

Hands-on experience with Microsoft Fabric or Azure Synapse/Data Factory

Strong experience with Fivetran or similar ELT tools

Experience handling high-volume datasets (hundreds of millions of records)

Proficiency in SQL, Python, and data modeling concepts

Strong understanding of Medallion architecture.

* Strong practical knowledge and interest in modern AI tools.

* Genuine curiosity and willingness to continuously learn.

* Ability to research, experiment, implement, troubleshoot and improve independently.

* Good understanding of prompting and AI workflows.

* Strong problem-solving mindset.

* Basic understanding of APIs, integrations and automation.

* Ability to explain technology clearly to non-technical people.

* Comfortable using AI to solve real-world business problems.

Roles & Responsibilities

• Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration

of enterprise-wide data from diverse sources

• Build and optimize data engineering workflows using Databricks and PySpark

• Write efficient, high-performance SQL for data transformation and analysis

• Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing,

data models, and pipelines

• Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the

development lifecycle

• Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production

environments with proper change control processes

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions

• Ensure data quality, reliability, and performance across all pipelines and platforms

Ideal Candidate

1Strong Azure Databricks Engineer / Senior Data Engineer Profile

2Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

As a Senior Data Engineer, you will be responsible for designing, developing, and optimizing scalable cloud-native data platforms on AWS. You will build high-performance batch and analytical data pipelines using DBT (Cloud + Core), AWS Glue, SMUS, Redshift, Python, MWAA, APIs, and other AWS services while ensuring reliability, scalability, and operational excellence.

The role requires strong expertise in data engineering, SQL optimization, distributed data processing, and cloud-native architectures.

Must Have Primary Skills

Data Engineering

• 3+ years of hands-on experience building large-scale AWS Data Engineering solutions.
• Strong experience designing scalable batch and streaming data pipelines on AWS.
• Experience implementing monitoring, logging, alerting, and observability for production data pipelines.
• Strong understanding of data quality, troubleshooting, debugging, and production support.

DBT & Data Warehousing

• Strong hands-on experience with DBT (Cloud + Core) (Highly Recommended).
• Hands-on expertise with Amazon Redshift for Data Warehousing and Analytics.

Programming & Querying

• Strong expertise in:
• SQL (Analytical Queries, Window Functions, Stored Procedures)
• Python
• Spark / PySpark
• Strong experience in Spark/PySpark performance tuning and optimization.

Lakehouse & Apache Iceberg

• Hands-on experience designing and implementing Lakehouse solutions using Apache Iceberg.
• Experience optimizing Apache Iceberg and Amazon Aurora PostgreSQL for performance and scalability.
• Strong understanding of:
• Data Modeling
• Partitioning
• File Formats
• Lakehouse / Data Lake Architectures

AWS Cloud Services

Hands-on experience with AWS services including:

• AWS Glue
• Amazon MWAA
• Amazon EMR
• Amazon Redshift
• Amazon S3
• Amazon Athena
• AWS Glue Catalog
• Amazon Aurora PostgreSQL
• AWS Lambda
• Amazon EC2
• Amazon DynamoDB
• Amazon API Gateway
• Amazon CloudWatch
• Amazon SQS
• Amazon SNS
• Amazon EventBridge
• AWS Secrets Manager
• AWS IAM

Development Practices

• Experience with CI/CD.
• Strong knowledge of Git.
• Familiarity with Data Engineering best practices.

Soft Skills

• Strong communication skills.
• Excellent problem-solving ability.
• Stakeholder management experience.

Preferred Certification

• AWS Data Engineer Associate or equivalent AWS Certification.

Good to Have Skills

• AWS Step Functions
• Terraform / Infrastructure as Code (IaC)
• Kafka
• Hive
• HDFS
• Other Big Data technologies
• Experience using GenAI-assisted development tools such as:
• GitHub Copilot
• Cursor
• Kiro
• Similar AI coding assistants
• ClickHouse Database
• Telecom / Mobile Network domain knowledge
• AtScale design and development
• Docker
• Kubernetes 

Hiring : Senior Databricks AI Architect

Exp : 15 - 18 yrs

Work Location : Pune WFO

Skills :

10 +years of experience in Data Engineering, Data Architecture, Analytics, or Software Engineering.

Minimum 5 years of hands-on experience with Databricks (Mandatory).

Strong expertise in designing and implementing enterprise-scale data platforms on Databricks.

Hands-on experience with AI-powered engineering tools such as Databricks Genie, Cursor, GitHub Copilot, or similar AI platforms.

Strong proficiency in Python, SQL, Spark, Delta Lake, and Databricks notebooks.

Excellent communication, stakeholder management

This role will be permanent with NAM info and deploy to client location Hyderabad & Pune.

Work Mode: WORK FROM OFFICE

Role Descriptions:

• Perform detailed data analysis and support business decision-making
• Gather and document business requirements and translate them into technical specifications
• Work closely with stakeholders to define data needs and reporting requirements
• Create user stories, functional specifications, and support UAT activities
• Ensure alignment between business objectives and data solutions

Required Skills:

• Strong expertise in SQL and data querying
• Proven experience in data analysis, requirement gathering, and stakeholder management
• Ability to translate business requirements into technical solutions and user stories
• Good understanding of data models, reporting, and analytics concepts

Skills: Business Analysis~ORACLE SQL

Locations: ~HYDERABAD~PUNE~

Desire candidate

• Candidate should have valid PF.

Experience: 4–6 Years

Domain: Automotive IoT | Connected Vehicles | Firmware & OTA

Core Stack: Rust | AWS | IoT Core | Apache Kafka | MemoryDB

Key Responsibilities  

OTA & Firmware Lifecycle  

• Co-own OTA firmware rollout operations across multi-ECU connected vehicle architectures.
• Design automated mechanisms to detect update failures, network interruptions, verification errors, and stalled deployments.
• Implement deterministic retry, recovery, and rollback mechanisms to ensure reliable firmware updates without vehicle bricking.
• Ensure firmware package integrity, signature validation, and data security throughout the OTA pipeline.

Data Engineering & Telemetry  

• Design and maintain real-time streaming pipelines for vehicle telemetry, heartbeats, OTA campaign status, and ECU state changes.
• Build high-throughput data services and workers using Rust for payload routing, processing, and verification.
• Use Apache Kafka and AWS IoT Core for real-time data ingestion and event streaming.
• Leverage AWS MemoryDB for Redis for low-latency fleet state, campaign progression, and session management.
• Build resilient pipelines capable of handling intermittent connectivity, noisy networks, and out-of-order data.

Monitoring & Analytics  

• Build real-time dashboards for fleet health, firmware versions, OTA campaigns, and update progress.
• Define and monitor key OTA metrics including success/failure rates, retry rates, failure categories, and completion time.
• Implement automated alerting and anomaly detection for unexpected failure spikes during staged or canary rollouts.
• Analyze logs, traces, and telemetry data to identify campaign bottlenecks, telemetry loss, and hardware-related failures.

Required Skills  

Mandatory  

• 4–6 years of experience in Data Engineering, Software Engineering, or IoT Backend Engineering.
• Strong hands-on experience with Rust for backend/data processing applications.
• Experience with AWS, particularly IoT Core, S3, ECS/EKS, and Lambda.
• Strong experience with Apache Kafka and real-time data pipelines.
• Hands-on experience with AWS MemoryDB for Redis or Redis Enterprise.
• Working knowledge of Python and SQL.
• Experience with MQTT, WebSockets, and HTTP/S protocols.
• Strong understanding of distributed systems, streaming data, and resilient data pipelines.

Preferred  

• Experience with firmware lifecycle management and OTA systems.
• Exposure to connected vehicles, automotive IoT, telemetry platforms, or connected hardware fleets.
• Experience with device shadows and fleet/device state management.
• Experience building telemetry dashboards using Power BI, Apache Superset, or custom dashboards.
• Experience with staged/canary deployments and automated failure recovery.

Primary Technology Stack  

• Languages: Rust, Python, SQL
• Cloud: AWS, IoT Core, S3, ECS/EKS, Lambda
• Streaming: Apache Kafka
• Caching & State: AWS MemoryDB for Redis, Redis
• IoT Protocols: MQTT, WebSockets, HTTP/S
• Analytics & Visualization: Power BI, Apache Superset
• Domain: Automotive IoT, Vehicle Telemetry, OTA, Firmware Management

Strong Databricks Architect Profile with end-to-end Lakehouse ownership

2

Mandatory (Experience 1) – Must have 10+ years of software engineering experience with atleast 5+ years in Data Engineering with hands on exposure to Databricks and strong ownership of end-to-end data pipeline development.

3

Mandatory (Experience 2) – Must have atleast 5+ years of expertise across the Databricks ecosystem — Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, Workflows, Unity Catalog

4

Mandatory (Tech skill 1) – Must have worked at architecture level, owning end-to-end design through deployment

5

Mandatory (Tech skill 2) – Must have strong experience with Python and SQL for data processing and Apache Spark for performance tuning & scalability

6

Mandatory (Tech skill 3) – Must have experience in large-scale data warehousing & advanced data modeling (3NF and dimensional) across batch and real-time systems

7

Mandatory (AI Exposure) – Must have at least a basic working understanding of how AI services or tools work

8

Mandatory (Communication) – Must have strong stakeholder management & requirement-gathering experience with US or UK clients

9

Mandatory (Company) – Must come from a B2B IT services or IT consulting background

10

Mandatory (Note) – CTC is inclusive of 5% variable

11

Preferred (Tech skill 1) – Azure Databricks or Azure data services experience (project runs on Azure DevOps)

12

Preferred (Tech skill 2) – MLflow or MLOps practices and AI use cases (RAG, AI/BI)

13

Preferred (Tech skill 3) – CI/CD, Databricks Asset Bundles (DABs) or equivalent packaging, Terraform or IaC, reusable deployment templates

14

Preferred (Integrations) – ServiceNow or enterprise system integrations

15

Preferred (Certifications) – Databricks (Data Engineer Associate or Professional, ML or GenAI tracks), Azure or AWS cloud certifications

Are you someone who can do whatever it takes to make sure user's are provided with best customer suppport possible for fastest growing consumer apps in India. If yes then this is job for you. Head team of 4-5 support executive with hands on attitude to find issues and make sure they are solved asap.

Note - If you need handholding to do your job then this job is not yours. Don't mind applying.

Key Responsibilities  

• Design, build, and optimize scalable data pipelines for AI/ML applications.
• Develop, train, evaluate, and deploy Machine Learning and Deep Learning models.
• Build production-ready LLM applications using Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases.
• Fine-tune open-source and foundation models using domain-specific datasets.
• Develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, and lifecycle management.
• Perform data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation.
• Develop APIs and AI services for production deployment.
• Collaborate with cross-functional teams to deliver scalable AI-driven solutions.
• Monitor model performance, troubleshoot production issues, and maintain technical documentation.

Required Skills  

Mandatory  

• 1–3 years of experience in Data Science, Data Engineering, or AI/ML development.
• Strong programming skills in Python and SQL.
• Hands-on experience with Machine Learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience building LLM-powered applications using RAG, Prompt Engineering, and Embeddings.
• Hands-on experience with LangChain, LlamaIndex, CrewAI, or n8n for LLM orchestration and AI workflow automation.
• Experience in LLM fine-tuning and working with Hugging Face models.
• Knowledge of MLOps concepts including model deployment, monitoring, versioning, and CI/CD.
• Experience with Git, REST APIs, Linux environments, and data processing libraries.

Preferred  

• Experience with vector databases such as Pinecone, Chroma, Milvus, or Weaviate.
• Familiarity with Docker, Kubernetes, and MLflow.
• Exposure to Apache Spark or Airflow for data engineering workflows.
• Experience with cloud platforms (AWS, Azure, or GCP).

Primary Technology Stack  

• Languages & Data Processing: Python, SQL, Pandas, NumPy, Apache Spark
• AI & Machine Learning: PyTorch, TensorFlow, Scikit-learn
• Application Frameworks: LangChain, LlamaIndex, CrewAI, n8n
• Core Methodologies: Retrieval-Augmented Generation (RAG), Model Fine-Tuning, Prompt Engineering, Embeddings
• Models & Infrastructure: OpenAI APIs, Hugging Face Ecosystem, Embedding Models
• Vector Databases: Pinecone, Chroma, Milvus, Weaviate
• Databases: PostgreSQL, MongoDB
• MLOps & DevOps: Docker, Kubernetes, MLflow, CI/CD, Git
• Cloud Platforms: AWS, Azure, GCP

Experience: 1–3 Years

Domain: Data Science | Data Engineering | Machine Learning | Generative AI | MLOps

About AuxoAI:

AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data. What We Do We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions.

We help our clients with accelerating their digital and AI journeys through:

• AI Application Development

• Data, Digital and Cloud acceleration using AI

• AI Native Product Engineering

We are seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have 6+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.

Responsibilities:

* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.

* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

* Implement data governance and security best practices to ensure compliance and data integrity.

* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Requirements :

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.

* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.

* Strong programming skills in languages such as Python, Java, or Scala.

* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.

* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.

Description:

Analytical Engineer with strong Data Analyst and Data Modelling expertise required to translate business requirements into structured, analytics-ready datasets. Must have experience in Data Vault 2.0 / dimensional modelling and advanced SQL for data transformation and analysis. Role focuses on data profiling, validation, and delivery of trusted data for reporting and analytics. Experience with Azure/Databricks and enterprise data environments preferred. Strong stakeholder engagement and ability to bridge business and technical data requirements essential.

Must Have Skills

• Data Analysis
• Data Governance
• Data Modeling tool

Nice to Have Skills

• Business writing skills
• Governance, Risk and Controls
• Principles of project management
• Relevant regulatory knowledge
• Relevant software and systems knowledge

Key Responsibilities

Build and maintain data transformation pipelines using java Spark

Develop and optimize large-scale/CPU intensive data processing using Apache Spark

Orchestrate workflows using Airflow

Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage

Support schema evolution, backfills, and incremental processing

Ensure pipelines meet SLAs for freshness, reliability, and performance

Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)

Required Skills & Qualifications

Strong hands-on experience with 

HBase

Apache Spark

Experience with HBase or similar lakehouse query engines

Airflow 

Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)

Proficiency in Java

Experience with Git-based development and CI/CD

Nice-to-Have Skills

OpenTable format/Iceberg ,Apache Arrow

CDC-based analytics pipelines

Cloud platforms (AWS)

Kubernetes-based data platforms

Company Name – Wissen Technology

Group of companies in India – Wissen Technology & Wissen Infotech

Work Location – Whitefield, Bangalore

Website and Company profile:

www.wissen.com

LinkedIn Page:

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

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology:

·    The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.

·    Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.

·    Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.

·    Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.

·    Globally present with offices US, India, UK, Australia, Mexico, and Canada.

·    We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.

·    Wissen Technology has been certified as a Great Place to Work®.

·    Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.

·    Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.

·    We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

About Role :

Key Responsibilities

• Build and maintain data transformation pipelines using java Spark
• Develop and optimize large-scale/CPU intensive data processing using Apache Spark
• Orchestrate workflows using Airflow
• Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage
• Support schema evolution, backfills, and incremental processing
• Ensure pipelines meet SLAs for freshness, reliability, and performance
• Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)

Required Skills & Qualifications

• Strong hands-on experience with 
• HBase
• Apache Spark
• Experience with HBase or similar lakehouse query engines
• Airflow 
• Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)
• Proficiency in Java
• Experience with Git-based development and CI/CD

Nice-to-Have Skills

• OpenTable format/Iceberg ,Apache Arrow
• CDC-based analytics pipelines
• Cloud platforms (AWS)
• Kubernetes-based data platforms

Experience Required: Minimum 8 Years

About the Role:

Key Responsibilities

• Design and manage organization-wide MIS reports, dashboards, and executive reports.
• Develop automated reporting solutions using Python, VBA Macros, Power Query, and Advanced Excel.
• Analyze large datasets and provide business insights to leadership.

Eligibility Criteria

• 5+ years of experience in Business Intelligence, MIS, Business Analytics, or Data Analytics.
• Strong analytical and logical thinking with the ability to understand business requirements and convert data into meaningful business insights.
• Experience in developing dashboards and management reports using any Business Intelligence tool (Power BI, Tableau, Zoho Analytics, etc.).

Apply Now:

https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort

Design, build, and maintain end-to-end data pipelines to ingest, process, and transform data from files, streams,

APIs, and relational/non-relational databases into Snowflake.   Develop and optimize ELT/ETL pipelines using Snowflake SQL,

Snowpipe, Streams & Tasks, and cloud-native orchestration tools.   Implement scalable data models and schemas (staging, curated, and consumption layers) to support analytics and reporting use cases.   Develop transformations and business logic using SQL and Python, including Snowflake UDFs and stored procedures.   Optimize Snowflake performance and cost through query tuning, warehouse sizing, clustering, and resource management.   Integrate Snowflake with cloud storage and services across AWS and Azure (e.g., object storage, data integration, and mess

Role Overview

We are looking for a hands-on engineering leader who can own technical design and drive end-to-end development of scalable, high-quality systems. This role requires strong architectural depth, coding excellence, and the ability to mentor engineers while building production-grade applications in a fast-paced agile environment.

You will lead by example — designing systems, writing clean code, solving complex problems, and ensuring engineering best practices across the stack.

Key Responsibilities

• Lead technical design and architecture discussions (HLD & LLD).
• Build scalable, modular, and testable systems with strong engineering fundamentals.
• Own complex features end-to-end — design, development, testing, and optimization.
• Write high-quality, production-ready code with strong unit test coverage.
• Ensure clean code practices (SOLID principles, modular design, reusability).
• Drive engineering quality within CI/CD environments.
• Debug and resolve complex issues across distributed systems and APIs.
• Mentor engineers and elevate overall code quality standards.
• Collaborate effectively within agile teams and move with delivery velocity.

Core Technical Requirements

• 8+ years of hands-on software development experience.
• Strong proficiency in:
• Java
• Node.js
• Angular (6+)
• JavaScript / TypeScript
• SQL & MongoDB
• Deep understanding of system design, architecture patterns, and scalable application development.
• Strong debugging capabilities across:
• Distributed services
• API integrations
• UI state management
• Database query performance
• Experience working in CI/CD-driven engineering environments.

GenAI & AI Stack Expertise

• Hands-on experience with GenAI frameworks and LLM integrations.
• Familiarity with:
• LangChain ecosystem
• Hugging Face
• Prompt chaining & orchestration
• Understanding of AI cost optimization strategies.
• Ability to debug AI pipelines and optimize model interactions.

Engineering Expectations

• Strong ownership mindset.
• Ability to design independently and lead technical direction.
• Exceptional problem-solving and debugging skills.
• High attention to detail.
• Comfortable working in fast-paced agile/scrum setups.
• Strong communication and collaboration skills.
• Ability to mentor and guide other engineers.

Educational Qualification

• Bachelor’s degree in Computer Science / Engineering / related field
• or
• Master’s degree in Computer Science / Computer Applications

Hiring for Prinipal / Lead Data Architect

Exp : 12 - 16 yrs

Work Location : Bengaluru

Shift Timings : UK

Mode of Interview : F2F

Skills :

Databricks, Python, Scala, SQL, Snowflake, Structured Streaming, Apache Kafka, Flink/AWS.

10+ years of progressive experience in Data Engineering, Data Warehousing, and Data Architecture.

What you'll need

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 5+ years of professional data engineering experience.
• Experience designing and building cloud-native data solutions.
• Strong expertise with Google Cloud Platform, including BigQuery. Experience developing transformation frameworks using dbt.
• Strong SQL and Python programming skills.
• Experience with PostgreSQL or other relational databases.
• Experience orchestrating workflows using Apache Airflow or Cloud Composer.
• Experience implementing Infrastructure as Code using Terraform. Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar platforms.
• Experience developing scalable batch and streaming data pipelines. Strong problem-solving skills with the ability to balance scalability, reliability, and cloud cost optimization.

Preferred Qualifications

• Experience with Pub/Sub, Datastream, Dataflow, Cloud Storage, Cloud Functions, or Cloud Run.
• Experience building multi-tenant SaaS platforms.
• Experience implementing metadata-driven governance, lineage, and data quality frameworks.
• Experience supporting AI, machine learning, or customer-facing analytics platforms.
• Experience with Kubernetes and Docker.

About the Role

We are looking for a hands-on Principal Engineer who owns enterprise integration architecture from end to end — from the first whiteboard sketch through production delivery and ongoing governance. This is not a management role, and it is not a specialist role. We are not looking for an Angular architect, a Java architect with cloud exposure. We need a true Full Stack Integration Architect who has designed, built, and governed how large-scale enterprise systems connect, communicate, and operate reliably at scale.

You will be expected to go deep on integration design, backend engineering, data architecture, cloud infrastructure, and front-end development — and to defend every decision under rigorous technical scrutiny. If your experience is anchored in one layer or one language, this is not the right opportunity.

What You Will Own

• End-to-end integration architecture across cloud platforms (AWS, Azure, GCP), on-premises systems, and third-party services — designed, delivered, and governed by you
• Definition and enforcement of integration patterns across the enterprise: API-first, microservices, event-driven, and real-time and batch processing
• Seamless data flow, application interoperability, and fault tolerance across mission-critical platforms
• Quality and testing strategy across integrated solutions — automation frameworks, release readiness, validation, and quality governance
• Full-stack engineering across all layers: front-end, backend services, data, and cloud infrastructure
• GenAI and LLM integration into production-grade digital platforms
• Technical mentorship across engineering levels and cross-team architectural influence
• Clear communication of complex architectural decisions to both engineering teams and business stakeholders

What You Must Have

• 15+ years of hands-on software engineering experience with a strong track record in enterprise-scale distributed systems
• Proven end-to-end integration architecture experience — you have designed, governed, and delivered enterprise integrations across complex, heterogeneous environments; not just implemented someone else's design
• Genuine full-stack depth across all layers:
• Front-end: Angular, TypeScript
• Backend: Java, Python, Go, or Node.js — at least one deeply, others functionally
• Data: SQL, NoSQL, caching (Redis), event streaming platforms
• Strong database knowledge in both theory and practice — relational, NoSQL, distributed data, and streaming
• Cloud-native hands-on experience across at least one of AWS, Azure, or GCP — Kubernetes, Docker, and Infrastructure as Code (Terraform) are expected
• CI/CD pipeline experience tied to enterprise release cycles and quality governance
• The ability to clearly articulate the technical design, tradeoffs, and problem-solving approach behind your own recent work — this will be probed in depth during interviews

Integration & API Technologies

You should have hands-on experience across several of the following:

REST · GraphQL (Apollo Federation or similar) · gRPC · Kafka or equivalent event streaming · Microservices architecture · Event-driven architecture · B2B and internal system integrations · Real-time and batch integration patterns

What Will Strengthen Your Profile

• GCP-native database experience: BigQuery, Spanner, Bigtable
• Production-grade GenAI or LLM integration — not just prototypes or proof of concepts
• Experience with AI development tools: Cursor, GitHub Copilot, Vertex AI Studio, Claude Code
• Healthcare or regulated-industry platform experience
• MLOps or AI lifecycle management
• Identity, security, and privacy architecture at enterprise scale
• Observability tooling: Datadog, Prometheus, Grafana

Do Not Apply If

• You are primarily an Angular Architect, a Java architect, or strong in one layer only — this role demands genuine end-to-end depth across the full stack
• You cannot walk through the architecture, implementation decisions, and tradeoffs of your own recent projects with technical precision
• You have not designed or governed integrations at enterprise scale across distributed, heterogeneous systems
• Your backend, database, or integration experience is surface-level, theoretical, or limited to a single technology

Why This Role

This role carries real architectural authority at a large enterprise. You will set integration direction across business-critical platforms, influence engineering standards, and solve problems that matter at significant scale. The technical bar is deliberately high — because the impact is real.

Job Summary

We are seeking a skilled Azure Data Engineer with hands-on experience in Azure Data Services, Azure Databricks, Python, PySpark, and SQL. The ideal candidate will be responsible for designing, developing, and optimizing scalable data pipelines and data processing solutions to support business intelligence, analytics, and reporting requirements.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks and PySpark.
• Build and optimize data processing workflows using Python and SQL.
• Develop and manage data ingestion pipelines from multiple structured and unstructured data sources.
• Work with Azure Data Factory (ADF) to orchestrate and schedule data pipelines.
• Implement data transformation and cleansing logic using PySpark.
• Optimize SQL queries and Spark jobs for performance and scalability.
• Collaborate with data architects, analysts, and business stakeholders to understand data requirements.
• Ensure data quality, integrity, and governance across the data platform.
• Monitor, troubleshoot, and resolve production data pipeline issues.
• Follow coding standards, version control, and CI/CD best practices.

Required Skills

• Strong experience with Microsoft Azure cloud services.
• Hands-on experience with Azure Databricks.
• Strong programming skills in Python.
• Expertise in PySpark for large-scale data processing.
• Strong SQL skills, including query optimization and performance tuning.
• Experience with Azure Data Factory (ADF).
• Knowledge of Delta Lake, Spark SQL, and Databricks notebooks.
• Experience with Git or Azure DevOps for source code management.
• Understanding of data warehousing concepts and ETL/ELT processes.

Preferred Skills

• Experience with Azure Synapse Analytics.
• Knowledge of Delta Live Tables (DLT).
• Experience with Azure Data Lake Storage (ADLS Gen2).
• Familiarity with Unity Catalog and data governance.
• Exposure to CI/CD pipelines and infrastructure-as-code.
• Experience working in Agile/Scrum environments.

Location: Bangalore / Hybrid

Duration: 6 months

Internship type: Full-time

Stipend: ₹20,000 per month

Potential outcome: Full-time opportunity based on performance

About the Role

We are looking for a hands-on Supabase Engineering Intern to help build and strengthen the backend of our SaaS products.

You will work with Supabase not merely as a hosted database, but as a complete backend platform—including PostgreSQL, authentication, Row-Level Security, storage, database functions, migrations, and application integrations.

This is a full-time, six-month internship suited to someone who has already built projects using Supabase and wants experience working on a real multi-tenant production application.

What You Will Work On

• Design and maintain PostgreSQL tables, relationships, indexes, and constraints.
• Implement secure multi-tenant access using Supabase Row-Level Security policies.
• Integrate Supabase Auth with a Next.js and TypeScript application.
• Build backend workflows using database functions, triggers, RPCs, and Edge Functions.
• Manage schema migrations across development and production environments.
• Work with Supabase Storage and implement secure file-access policies.
• Diagnose slow queries and improve database performance.
• Build reliable application APIs and data-access layers.
• Write seed data, automated tests, and technical documentation.
• Help investigate and resolve production database, authentication, and permission issues.
• Review existing implementations for data leakage, incorrect RLS policies, and security risks.

Required Skills

• Practical experience building at least one project using Supabase.
• Good understanding of SQL and relational database fundamentals.
• Familiarity with PostgreSQL tables, joins, indexes, constraints, and transactions.
• Experience with JavaScript or TypeScript.
• Basic experience with Next.js, React, Node.js, or another modern web framework.
• Understanding of authentication and authorization concepts.
• Ability to use Git and GitHub.
• Strong debugging and problem-solving skills.
• Ability to commit full-time for the complete six-month internship.

Good to Have

• Experience implementing Supabase Row-Level Security policies.
• Understanding of multi-tenant SaaS architecture.
• Experience with Supabase Edge Functions, database functions, triggers, or RPCs.
• Familiarity with PostgreSQL query optimization and EXPLAIN ANALYZE.
• Experience managing Supabase migrations through the CLI.
• Knowledge of REST APIs, webhooks, background jobs, or third-party integrations.
• Experience using AI coding tools such as Cursor, Claude Code, or Codex.
• Contributions to open-source projects or independently deployed applications.

Who Should Apply

You may be a good fit if you:

• Have built and deployed a working Supabase application.
• Enjoy backend engineering, databases, and debugging.
• Can explain why you structured your database and access policies in a particular way.
• Are comfortable learning through documentation and experimentation.
• Take ownership instead of waiting for detailed instructions for every task.
• Want meaningful product-engineering experience rather than a certificate-based internship.

What You Will Learn

• How production-grade multi-tenant SaaS applications are designed.
• Secure database access using PostgreSQL Row-Level Security.
• Development-to-production database migration workflows.
• Authentication, authorization, storage, and backend architecture.
• Performance optimization and production debugging.
• How a startup engineering team ships and operates real products.

Application Process

To apply, please share:

1. Your resume.
2. GitHub profile.
3. Links to one or two relevant projects.
4. A short explanation of how you used Supabase in one project.
5. An example of an RLS policy, database function, or Edge Function you have written.
6. Your current location and availability.
7. Confirmation that you can commit full-time for six months.

Important: Tutorial-only projects will not be sufficient. We are looking for candidates who can demonstrate that they understand the database and security decisions made in their projects.

Who are we?

Trendlyne is a funded, profitable products startup in the financial markets space. We have cutting-edge analytics products built for Indian and US customers, for stock markets and mutual funds.

Our founders are IIT + IIM graduates, with strong tech and marketing experience. We have top finance and management experts on the Board of Directors.

What do we do?

We build powerful analytics in the US and Indian stock market space that are best in class. Organic growth in B2B and B2C products have already made the company profitable. We deliver 1 billion+ APIs every month to B2B customers, and have a B2C website and app.

Tech Stack :

• Postman
• Playwright
• Jenkins

Job Responsibilities :

• Design, develop, and maintain scalable UI and API automation frameworks from scratch.
• Build and execute automated test suites for frontend, backend, and API applications using tech stacks like Playwright, Selenium, and Postman.
• Develop automation for web applications, APIs, and distributed microservices.
• Perform white-box and black-box testing to ensure application quality.
• Integrate automation suites into CI/CD pipelines using tools like Newman and Bruno CLI.
• Identify, track, and resolve defects while improving test stability, execution speed, and overall automation efficiency.
• Collaborate with developers, DBAs, and product managers to ensure quality throughout the development lifecycle.
• Drive continuous improvements in automation frameworks, testing methodologies, and engineering processes.

Required Skills & Qualifications :

• 1-3 years of experience as an SDET, Automation Engineer, or Full-Stack QA.
• Experience with UI automation using Playwright and Selenium.
• Strong experience in API testing and automation using Postman.
• Proficient in JavaScript for building automation scripts, API test assertions, and test utilities.
• Experience with white-box and black-box testing, and automation design patterns such as Page Object Model (POM).
• Familiarity with BDD frameworks (e.g., Cucumber) and modern testing practices.
• Experience with Git and integrating automation suites into CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI.
• Working knowledge of SQL for database validation and backend testing.