Top Data Engineer Jobs in Pune

Lead and architect large-scale data engineering initiatives: design cloud-ready ELTL/real-time data platforms, drive AI adoption, ensure SLAs and quality across SDLC, mentor teams, and manage complex projects and vendor selections.

Lead technical design and build scalable data pipelines and platforms to support AI Ops, SRE, and analytics. Set standards for quality, security, and observability, mentor engineers, operationalize models, and contribute to roadmap and documentation for the ONE Data Lake.

Lead architecture and modernization of an enterprise-scale, multi-tenant rewards data platform. Define standards for data modeling, integration, security, and workflow orchestration; design scalable batch and real-time distributed processing; drive cloud migrations, observability, and operational excellence; mentor engineers and influence cross-team architectural decisions.

Administer and optimize Cloudera CDP/CDH platforms; develop and deploy PySpark/Python data processing; build CI/CD pipelines with Jenkins and GitHub/Bitbucket; integrate SAST tools; tune Hive/Impala SQL; monitor platform health, perform upgrades, troubleshoot, and implement security and governance controls.

Design and implement scalable end-to-end data pipelines and storage schemas across cloud and on-prem platforms. Define reference architectures and engineering standards, ensure governance/security/compliance by design, optimize performance for large datasets, and mentor/lead global teams using Python/Java, SQL, Spark, Databricks, and related data platforms.

Design, build, and maintain scalable data pipelines and cloud data platforms to support AI/ML workloads. Deploy, monitor, and operationalize machine learning models, implement CI/CD and MLOps, ensure data quality, scalability, and governance while collaborating with data scientists, engineers, and stakeholders.

The Senior Software Engineer - Data Engineer will lead project phases, design technical solutions, manage team efforts, and collaborate globally while driving innovative data solutions.

Design, build, and maintain cloud-native data pipelines and ETL/ELT workflows for high-volume trade lifecycle data. Integrate DTCC sources (RTTM, Settlement Web) into a Unified Trade Record, process ISO 15022 messages, manage trade exception databases, optimize SQL Server performance, and ensure data quality, lineage, governance, and observability while collaborating with business stakeholders.

This role entails testing and validating big data platforms focusing on real-time and batch processing, ensuring data correctness and system reliability.

Design, build, and maintain cloud data pipelines, warehouses, and lakes on AWS and Snowflake. Develop ETL/ELT, data transformations, ingestion, and reusable components, collaborate with data scientists on ML deployment, and ensure data governance, security, and operational excellence.

Design, build and maintain data pipelines, data warehouses and data lakes on AWS. Develop processing and analysis algorithms, collaborate with data scientists to deploy ML models, lead or support a team, ensure data security, accuracy and compliance, and drive continuous improvement.

Design, build and maintain data pipelines, warehouses and lakes on AWS. Ensure data quality, security and accessibility. Develop processing algorithms, collaborate with data scientists to deploy ML models, and lead/coach teams while managing risk and controls.

Design, build and maintain data pipelines, warehouses and data lakes on AWS. Develop processing and analysis algorithms, ensure data accuracy, security and governance. Collaborate with data scientists to deploy ML models. Lead or coach teams, advise on policy, mitigate risk and communicate complex technical information to stakeholders.

The AI Data Engineer will build and maintain data systems, design data architectures, collaborate with data scientists, and advise on strategies for data management and governance.

Design, build and maintain data pipelines, warehouses and lakes. Implement processing and analysis algorithms, ensure data security and quality, collaborate with data scientists to deploy ML models, and lead or mentor team members while partnering with stakeholders.

Build and maintain data pipelines, data warehouses and data lakes; ensure data accuracy, accessibility and security; develop processing and analysis algorithms; collaborate with data scientists to deploy ML models; lead or coach teams and influence stakeholders on risk, controls and policy.

Design, build, and maintain data pipelines, warehouses and lakes; ensure data accuracy, security and scalability; develop processing and analysis algorithms; support ML model deployment; lead or coach team members and influence cross-functional decisions while managing risk and controls.

Design, build, and maintain scalable Snowflake and Python data pipelines integrating cloud and on-prem sources. Implement data transformation, validation, reconciliation, and quality checks; automate workflows and shell scripts; optimize performance and security; collaborate with distributed Agile teams; troubleshoot pipelines; document architectures and operational procedures; and support production deployments and cost-efficient cloud operations.

Design, build, and maintain large-scale data platforms and pipelines to support analytics and ML; optimize performance, ensure data quality, collaborate with data scientists, and support production deployments.

Lead design and implementation of an Analytic Foundation and scalable big-data services delivered via APIs. Build data pipelines, analytics and data models, responsive UIs, and production ML/data-driven applications. Ensure high-quality, well-tested code, mentor junior engineers, drive process improvements, and collaborate with product and design teams to deliver customer-focused data solutions.

As a Data Engineer, you will develop and maintain data systems, build pipelines, design data architectures, and collaborate with data scientists to implement machine learning models.

Design, build, and maintain scalable AWS-based data enrichment pipelines (Spark) and orchestrations (Airflow); use S3/Glue/Athena for storage, processing and querying; perform deep data quality analysis, implement validation/observability, troubleshoot tracking and delivery issues across hybrid systems, and collaborate on governance, lineage, and schema design to support media measurement and audience intelligence.

Design, develop, and maintain ETL/data pipelines using Microsoft Fabric and Azure. Build and optimize OneLake/Lakehouse solutions, integrate multiple data sources, implement transformations with SQL, Python, and PySpark, ensure data quality and performance, collaborate with stakeholders, and maintain documentation.

Join the AI Innovation at Scale team to design and execute test strategies, perform white-box and black-box testing, validate data using Impala and Spark, monitor Spark job execution, collect logs, analyze quality data, and work with stakeholders to resolve issues and improve QA processes.

Design, build and maintain data pipelines, warehouses and lakehouse architectures; migrate Ab Initio workloads to cloud (AWS/Databricks/Spark); optimize performance and scalability; lead modernization initiatives; mentor engineers; collaborate with data scientists and stakeholders to deploy ML models and ensure data reliability, security and governance.