Top Data Engineer Jobs in Mumbai

Design, develop, maintain, and optimize scalable ETL pipelines and data workflows for a large-scale analytics platform. Ensure data reliability, manage production pipelines, resolve tickets within SLA, support P1/P2 incident resolution, and collaborate with data and application development teams. The role is based onsite in Mumbai and requires client site visits.

Build and operate ingestion and transformation pipelines to turn messy insurance data into clean datasets. Design bronze/silver/fact layers, model and tune Postgres and analytical stores, define KPIs and reconciliation checks, orchestrate observable data jobs, and ensure end-to-end data quality for analytics and AI products.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

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, build, and maintain dbt models and Snowflake data warehouses, own CI/CD and orchestration for pipelines, implement data quality tests, partner with stakeholders to translate requirements into production-ready data models, and optimize performance and observability.

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

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

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.

Design and build a greenfield, multi-layer data warehouse and semantic metrics layer; separate analytics from OLTP; ensure data quality, traceability, tenant isolation, and high SLAs; enable linking of structured records to drone imagery/video; deliver self-service data access, observability, and infrastructure automation to scale across products and tenants.

The Senior Tableau Consultant focuses on data visualization development, project management, mentoring, and supporting business requirements using Tableau. Responsibilities include dashboard architecture, user configuration, and training.

Design, build, and maintain cloud-based data infrastructure and pipelines; develop, train, and deploy AI/ML models; collaborate with cross-functional teams to productionize models, ensure data quality, scalability, and monitoring.

Design, develop, and maintain scalable analytics solutions on the Looker BI Platform, focusing on LookML modeling and collaboration with data engineers and stakeholders.

The Senior Data Engineer will build and maintain data ingestion pipelines, manage FHIR serialization, and work within a spec-driven development framework, ensuring operational stability and high data quality for healthcare data workloads.

Own the architecture, scalability, governance, and technical direction of Amtech’s cloud data platform, including warehouses, tenant data stores, feature stores, and event pipelines. Lead multi-tenant data architecture, hybrid AI data routing, data security, observability, and reliability standards. Build data foundations for analytics, machine learning, and AI agents, including vector databases and RAG pipelines. Provide technical leadership through design reviews, mentoring, roadmap planning, and cross-functional architecture collaboration.

Migrate SQL Server data products and analytical workloads to a modern cloud platform. Redesign legacy SQL, ETL processes, and business logic; build scalable pipelines and analytical models; validate data quality; collaborate with stakeholders; and improve platform reliability, performance, cost efficiency, and AI-assisted data engineering automation.

Build and maintain Snowflake and SQL Server data pipelines for an operational data store, including ingestion, transformation, schema modeling, migrations, CI/CD, data quality testing, and legacy batch-to-API modernization. Collaborate with domain teams and architects to support customer, loan, payment, and interaction data. Ensure data accuracy, lineage, observability, and performance while applying generative AI tools to accelerate development and testing.

The role involves building and scaling the Acceldata Open Data Platform, focusing on observability, coding, debugging, and collaborating with teams and the open-source community.

Build and enhance enterprise data pipelines into Databricks Unity Catalog and Delta Lake. Improve remediation and entity-matching layers (including D&B DataBlocks), integrate APIs, and support LLM-assisted remediation and CMG redesign projects.

Design and implement distributed data systems for Apache Hudi and Onehouse’s managed data lakehouse. Responsibilities include developing concurrency controls, transactional capabilities, indexing schemes, metadata and data-access systems, and optimization algorithms for Kubernetes-based distributed processing. The role involves analyzing complex data, prototyping performance improvements, deploying solutions safely to production, and serving as a subject matter expert in databases, query engines, storage, and stream processing.

Build and productionize distributed data infrastructure for Onehouse’s managed lakehouse platform. Responsibilities include developing Apache Hudi transactional capabilities, concurrency control, indexing, metadata and data-access systems, and optimization algorithms for distributed processing on Kubernetes. The role involves analyzing complex data, prototyping performance improvements, collaborating with engineers, and safely deploying solutions. Candidates should bring strong object-oriented programming, distributed systems, algorithm, and relational database expertise.

Leads data management and quantitative analysis strategy, ensuring data integrity, accuracy, and governance across platforms. Translates complex data insights into business strategies, drives process automation and continuous improvement, and collaborates cross-functionally to support data-driven decisions. The role also mentors team members, promotes innovation, and advances data management practices through emerging technologies and industry trends.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

The Data Engineer role involves designing and maintaining ETL pipelines, optimizing data storage solutions, collaborating with teams, and ensuring data accuracy and integrity.

Designs, builds, and maintains ETL/ELT pipelines feeding Microsoft Fabric Lakehouse platforms. Responsibilities include data ingestion, bronze/silver/gold layer development, CDC, incremental loading, data quality, metadata governance, performance tuning, monitoring, automation, and low-level design documentation. The role collaborates with architects, data modelers, and business analysts to deliver reliable, reusable datasets and promote self-service analytics while applying security, resilience, compliance, and cost-optimization standards.

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