Top Data Engineer Jobs in Pune

Design, build, and maintain data pipelines, warehouses and lakes; implement ETL and processing algorithms; ensure data security and observability; collaborate with data scientists to deploy ML models; lead or coach team members and influence cross-functional decisions.

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.

The Data Engineer will build and maintain data systems, develop ETL workflows, collaborate with data scientists, and ensure data accuracy and security.

Build, optimize, and monitor large-scale data pipelines using Databricks, Spark, and Delta Lake. Implement ingestion, transformation, and integration workflows, ensure data quality and performance, enable analytics with stakeholders, apply lakehouse and cloud best practices, and work in an Agile delivery model.

Lead technical direction for data platforms, design and maintain data pipelines for reporting and AI (RAG, embeddings, vector stores), reduce architectural debt, mentor engineers, partner with product leadership, and represent Mitratech externally.

The AWS Data Engineer builds and maintains systems for data collection, storage, processing, and analysis. Responsibilities include designing data architectures, collaborating on machine learning models, advising decision-making, and ensuring operational effectiveness.

Design, build, and maintain scalable ETL pipelines and data models for analytics and ML. Ensure data quality, optimize performance, enforce governance and security, and collaborate with stakeholders to deliver reliable, production-ready data for reporting and data science.

Design, build and maintain ETL mappings and data models; write SQL and Snowflake queries; manage ETL/infrastructure on AWS (EC2); use Informatica, Control-M and ServiceNow; script in Python/Shell/PowerShell; collaborate with onshore/offshore teams and define BI delivery strategy.

Design, build, and maintain cloud-based ETL/data pipelines in Snowflake. Extract and transform data from heterogeneous sources, optimize SQL performance, implement monitoring, and collaborate across teams. AWS and Python experience are advantageous.

Design, build, and maintain cloud data pipelines and architectures using SQL, Python, Snowflake, and AWS. Implement CI/CD for data workflows, use developer assistance tools, and collaborate across teams to deliver reliable data solutions.

Design, develop, and coordinate cloud data solutions using Snowflake, Python, and AWS. Support product releases, deployments, testing, and post-install support. Collaborate with architects and tech leads, troubleshoot issues, and maintain documentation. Contribute to agile squads, adopt new technologies, and enable Fidelity Wealth business data needs.

Develop and maintain data pipelines and applications using Python and Pandas, apply OOP and data structures, write and optimize SQL, and communicate with stakeholders. Familiarity with Agile, DevOps/CI-CD tools (Jenkins, Git, Jira), AWS, web frameworks (Django/Flask), and Snowflake is a plus.

Design, develop, and optimize PL/SQL artifacts and Python ETL scripts; tune SQL and Oracle performance; ensure data integrity and availability; integrate systems via APIs; support production deployments and monitoring; collaborate with engineers and analysts; administer Oracle and PostgreSQL; use GitLab and Jira for version control and tracking.

Lead database design, data modeling, migrations, and schema evolution across MySQL/Postgres and GCP databases. Design and operate config-driven ETL/ELT pipelines and streaming ingestion, enable CI/CD, troubleshoot data flows, and mentor offshore DB/ETL engineers.

Perform data migration/refresh from production, support Python-based data refresh framework, run post-migration fixes, validate and reconcile data, monitor and resolve batch jobs and pipeline issues, perform performance checks, and coordinate with dependent teams.

Design, build, and maintain ELT/data pipelines and workflow orchestration using Airflow, Python, and PySpark. Develop custom connectors, implement DataOps and CI/CD for data, monitor and validate data flows, collaborate with cross-functional teams, and document data workflows and governance.

Design, develop, and optimize ELT/ETL pipelines and data models using SQL, Python, and cloud services (AWS). Enable cloud data movement to Snowflake, perform SQL performance tuning, support code migrations, and collaborate in agile, distributed teams to deliver analytics-ready data solutions.

Design, build, and maintain scalable ELT/data pipelines and connectors using Airflow, Python, and PySpark. Implement DataOps and CI/CD for data workflows, monitor and troubleshoot pipelines, validate data quality, collaborate with cross-functional teams, and document data processes and governance.

Join the Event Streaming and Data Replication platform as a Data Engineer to design, build, and operate cloud-native data platforms. Work with Airflow, Spark, Kubernetes, and Python; deploy containerized apps on AWS/Azure; use IaC (Terraform/CFT/ARM); implement CI/CD (GitHub, Artifactory, Jenkins); configure monitoring and alerts; and collaborate across teams to deliver highly available, scalable solutions.

Design, build, and maintain ELT/data pipelines and workflow orchestration using Airflow, Python, and PySpark. Develop custom connectors to ingest diverse data, implement DataOps and data CI/CD pipelines, monitor and troubleshoot pipelines, validate data quality, collaborate with cross-functional teams, document workflows, and work with large-scale distributed datasets and visualization tools.

Design, build, and maintain scalable data pipelines and ETL processes using Python and PySpark. Orchestrate workflows with Airflow, query data with Trino and Hive, and write efficient SQL. Collaborate in Agile/Scrum teams to deliver data solutions and optimize data platform performance.

Design, build and optimize ETL pipelines and cloud data workflows using Python, PySpark, AWS Glue and Lambda. Implement data models and schemas in PL/SQL/PostgreSQL, integrate AWS services (SNS, Step Functions), and troubleshoot pipelines for performance, scalability and reliability.

Design, build, and maintain cloud data pipelines and streaming solutions using Java, Kafka, AWS services, SQL/warehouse technologies, and Python. Implement CI/CD, automated testing, and resilient microservice-based systems. Collaborate in a small agile team and ensure secure identity/authentication controls.

Design, build, and maintain ETL pipelines and frameworks on AWS. Deploy and troubleshoot containerized applications (Docker, EKS), support CI/CD and build tooling, work with SQL/Oracle and ORM tools, and use job schedulers like Autosys/Airflow. Collaborate in Agile/SCRUM environments.

Design, implement and maintain high-volume online and offline batch and transactional data applications using Java and Spark. Build scalable data stores, write scripts, call APIs, and author complex SQL. Maintain code and database infrastructure, ensure data integrity, perform data cleaning, visualization and reporting, and support model training in an agile environment.