Top Data Engineer Jobs in Mumbai

This role involves leading the design, build, and operation of enterprise data platforms using AI/ML, ensuring scalability and compliance while providing technical leadership and collaborating across teams.

Senior GIS Data Engineer responsible for developing and maintaining geospatial datasets and data pipelines. Build, run, and optimize ETL workflows (batch to flow), transform and integrate spatial data using FME/ArcGIS/Python/SQL, ensure data quality, provide GIS consultancy, and collaborate cross-functionally to deliver scalable mapping solutions and improve processes.

The Data Engineer will design, develop, and maintain ETL/ELT data pipelines, leveraging PySpark and Databricks to process large datasets, ensuring data quality, reliability, and performance optimization.

Design, develop, and maintain data solutions and ETL pipelines using Databricks. Ensure data quality, governance, and secure deployments. Lead and mentor teams, drive responsible AI practices, liaise with stakeholders, and implement scalable, transparent AI solutions.

Design, develop and maintain data solutions and ETL pipelines on Databricks. Ensure data quality, implement cloud-based data engineering, enforce responsible AI and compliance, lead and mentor teams, and drive cross-functional collaboration on ethical AI practices.

Design, build, and maintain Azure-based data solutions and ETL pipelines. Ensure data quality, migrate and deploy data across systems, optimize workflows, document processes, troubleshoot data issues, and mentor junior team members while collaborating with cross-functional teams.

Develop and maintain data pipelines using AWS technologies. Collaborate with teams to design data solutions and optimize existing systems. Create data models and perform end-user querying.

Design, develop, and maintain data solutions and ETL pipelines using Databricks. Ensure data quality, optimize pipeline performance, collaborate with data scientists and analysts, and support data migration and storage across systems. Serve as an SME and contribute to team problem-solving and discussions.

The AWS Data Engineer will develop and maintain data pipelines using AWS technologies, perform data modeling, and collaborate with teams to meet data needs.

The Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality and collaborating across teams to prioritize data needs.

The role involves managing data pipelines in cybersecurity, collaborating with teams to implement solutions, and troubleshooting issues efficiently using Python and SQL.

The role involves leading data architecture and engineering for a health insurance platform, focusing on cloud-native solutions, scalable data pipelines, and ensuring data quality and governance while collaborating across teams.

As an Associate Data Engineer, you will modernize data systems, support real-time data processing, and analyze data to improve performance and customer acquisition.

Seeking an AWS Data Engineer to design and build data pipelines, ensuring data integrity and collaborating with various teams to enhance data solutions.

As a Data Engineer, you will innovate and maintain technology services, develop software systems for large projects, and work across all SDLC phases.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

Design, develop, and maintain data-driven applications for trading operations. Build data pipelines, optimize code, and collaborate with teams for solutions.

Lead design and implementation of end-to-end data pipelines and migrations, liaise with stakeholders, automate ingestion/transformation of batch and real-time structured and unstructured data, enforce data governance and quality, document data models and rules, migrate pipelines to AWS PaaS, drive process improvements, and manage full software lifecycle for ETL solutions.

As a Data Engineer, you will build scalable ETL/ELT pipelines, optimize data structures, and develop impactful Power BI solutions for stakeholders.

The role involves designing and building data systems using various technologies, especially within Microsoft Azure, and requires experience in system integration and data warehousing.

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, 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.

Build and maintain BigQuery data pipelines, map warehouse schemas, and craft SQL to feed LLMs. Develop Claude Skills and Gemini Gems, collaborate on prompts, validate AI outputs, and design AI agents to automate eCommerce analytics and operational workflows.

The Engineering Manager leads the Data Engineering team, overseeing the design of scalable data pipelines using AWS technologies, mentoring engineers, and collaborating with stakeholders on data-first initiatives.