Top Data Engineer Jobs in Mumbai

The SDET will develop and maintain automated testing frameworks, perform white-box testing, ensure test automation in CI/CD pipelines, collaborate on QA practices, and advocate for quality across teams.

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and cloud-native data services. Ensure data quality, optimize performance, mentor junior engineers, and collaborate across teams to deliver enterprise-grade data solutions.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, and cloud-native data services. Ensure data quality, performance tuning, and governance. Lead and mentor team members, collaborate across teams, and continuously improve data engineering practices using Python and multi-cloud technologies.

Entry-level Data Engineer in Technology & Operations supporting system design, implementation, and support. Build and maintain data pipelines, ETL processes, database solutions, and distributed/cloud systems. Work on data quality, automation, monitoring, and collaborate with cross-functional teams while learning security, DevOps, and emerging technologies like GenAI and cloud data platforms.

Entry-level graduate role in DBS Technology & Operations supporting system design, implementation, data engineering, ETL and system reliability. Work includes cloud, distributed systems, API management, automation/DevOps, troubleshooting, and collaboration across product and business teams. Opportunity to learn GenAI, Cloud Data Platform, and machine-learning implementations while supporting banking product launches and operations.

Campus-hire Data Engineer focused on data quality and technology operations: design and implement scalable systems, build data pipelines/ETL, support production systems, troubleshoot incidents, and work with cloud, API management, distributed systems, and automation. Participate in DevOps practices, data platform setup, and cross-functional projects across banking products while learning security, risk management, and emerging tech like GenAI and ML.

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and cloud-native data services. Ensure data quality, performance tuning, and governance; mentor junior engineers and collaborate across teams to deliver robust, cost-efficient data solutions.

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data services. Ensure data quality, performance tuning, and cloud-native deployments while mentoring team members and collaborating across teams to deliver robust, low-latency data solutions.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, and cloud-native data services. Ensure data quality, performance tuning, and governance. Lead and mentor team members, collaborate across teams, and continuously optimize data workflows for large-volume, low-latency processing in multi-cloud environments.

Design, develop, and maintain scalable data pipelines using Databricks or MS Fabric, ensuring data quality, integrity, and security across applications while optimizing data processing workflows and collaborating with cross-functional teams.

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and cloud-native data services. Ensure data quality, performance tuning, and governance. Lead and mentor team members, collaborate across teams, and optimize data workflows for reliability and cost efficiency.

Design, build, and optimize high-throughput ETL/ELT pipelines (Glue/PySpark), orchestrate workflows (Airflow/Step Functions), manage and tune multi-terabyte Redshift clusters, lead migrations from Snowflake/RDBMS, integrate heterogeneous sources, implement monitoring and governance, and collaborate with stakeholders to deliver analytics-ready datasets.

As a Data Engineer, design and maintain data solutions, create pipelines, ensure data quality, and implement ETL processes to facilitate data migration across systems.

Design, build, and maintain scalable Snowflake data pipelines and ETL/ELT processes. Ensure data quality, performance tuning, and security using Snowpipe, Streams, Tasks, and stored procedures. Collaborate with architects, engineers, and business teams, contribute to CoE guidelines, and support POCs. Mentor delivery teams and stay current on Snowflake and GenAI capabilities.

Design, build, and maintain Snowflake-based data architectures and ETL pipelines. Lead Snowflake solution design, data modeling, performance tuning, security, mentoring, presales, and POCs across projects.

Design, develop, and maintain Snowflake-based data architectures and ETL pipelines. Lead Snowflake solutions for ingestion, storage, transformation, and access; define data modeling standards; mentor teams; drive POCs, presales, and best practices; ensure performance, security, and integration across systems.

Build and maintain scalable Snowflake data pipelines and ETL/ELT processes, ensure data quality and security, tune performance, write advanced SQL, collaborate with architects and teams, support CoE initiatives, and contribute to POCs/POVs across projects.

Design, implement and maintain Snowflake-based data architectures and ETL pipelines. Lead ingestion, storage, transformation and access best practices, mentor teams, support presales, run POCs, and ensure data quality, security, performance tuning and governance across projects.

Design, build and maintain scalable Snowflake data pipelines and ETL/ELT processes. Ensure data quality, performance tuning, and security. Collaborate with architects and business teams, support CoE initiatives, and contribute to GenAI POVs/POCs using Snowflake and Cortex LLM capabilities.

Design and lead Snowflake architectures and data solutions, build ETL/data pipelines, ensure data quality and security, mentor teams, drive CoE initiatives, support presales and run POCs/POVs including GenAI integrations leveraging Snowflake Cortex and related tools.

Design, build and maintain scalable Snowflake data pipelines and ETL/ELT processes. Ensure data quality, performance tuning, advanced SQL, and security. Support CoE initiatives, collaborate with architects and teams, and enable delivery through best practices and POCs.

Design, develop, and maintain data solutions and ETL/data pipelines. Ensure data quality and governance, optimize data models and warehouses, troubleshoot pipelines, and lead teams to deliver cross-functional data solutions.

Design, build, and maintain scalable ETL/ELT pipelines using BigQuery and GCP. Integrate multiple data sources, optimize BigQuery performance (partitioning/clustering), support real-time and batch processing with Dataflow/Pub/Sub/Airflow, enforce data governance and quality, collaborate with analysts and data scientists, and troubleshoot pipeline reliability and availability.

Design, develop, and maintain scalable ETL/ELT pipelines using Python and PySpark. Optimize and manage large datasets in Google BigQuery, ensure data quality, build job orchestration with Airflow, write efficient SQL, and collaborate with data scientists, analysts and product teams to deliver analytics-ready data and documentation.

Design, develop, and optimize AWS Glue ETL pipelines integrating data from S3, RDS, Redshift, and other AWS services. Transform data into analytics-ready formats, ensure data quality and security, tune performance, orchestrate workflows (Step Functions/Airflow), monitor jobs, and collaborate with analysts and stakeholders to deliver scalable data lake and warehouse solutions.