Top Data Engineer Jobs in Mumbai

Design and implement cloud-native data lakes, warehouses, AI architectures, ETL/ELT pipelines, and real-time data systems. Guide architectural patterns, optimize performance and costs, align technical delivery with business goals, support client workshops, and mentor junior team members. The role requires expertise across major cloud platforms, data engineering tools, infrastructure as code, AI algorithm evaluation, and cloud solution architecture.

Designs, develops, and maintains scalable data architectures, ETL pipelines, data lakes, warehouses, data models, and data catalogs. Builds data solutions using Azure Data Factory, Azure Data Lake, Databricks, Scala, .NET, Python, and PySpark. Partners with data scientists, business stakeholders, analysts, and architects to deliver analytics-ready data products, establish governance and standards, mentor professionals, evaluate emerging tools, and support strategic enterprise initiatives.

Develop data-driven solutions by translating business problems into data problems, collecting and preparing data, building and evaluating statistical and mathematical models, and deploying models into applications. Manage data security, privacy, quality, availability, governance, migration, and policy. Operate and troubleshoot ELK environments, distributed clusters, Linux systems, and cloud infrastructure while communicating technical insights to diverse stakeholders.

Build and lead scalable batch and real-time data pipelines on AWS for security telemetry, analytics, detection, and AI/ML use cases. Develop Python frameworks, data models, and data products while ensuring quality, reliability, observability, and security. Collaborate with data scientists and engineers to productionize models, integrate enterprise security platforms, and implement DevOps, CI/CD, automation, infrastructure-as-code, and encryption practices. Own technical strategy and the end-to-end data engineering lifecycle.

Design and develop scalable data-driven solutions and pipelines using Python and SQL. Leverage Azure data services to build secure, high-performance architectures, ensuring data integrity, governance, and overall success of data projects.

Design and build scalable data pipelines and architectures on Azure using ADF, Databricks, and Synapse. Implement Kimball/Data Vault modeling, write ETL in Python and T-SQL, ensure data governance (Azure Purview), automate tests, troubleshoot issues, document processes, and collaborate across teams.

Design and develop data-driven solutions and scalable data pipelines using Python and SQL. Leverage Azure data products to build robust, secure architectures, ensuring data integrity, performance, and governance while supporting data-centric client projects.

Partner with investment, operations, and finance teams to translate business needs into BI dashboards, reporting, automation, and AI-enabled analytics using Power BI and SQL. Identify reporting gaps, capture requirements, and support adoption of AI-driven insights while liaising between business stakeholders and technical teams.

Designs, develops, and governs enterprise data platforms using Databricks and Microsoft Fabric. Builds scalable pipelines, lakehouses, warehouses, semantic models, data marts, automation frameworks, and data-quality validation systems. Leads data engineering through the full delivery lifecycle, implements security and governance controls, supports CI/CD and infrastructure automation, optimizes Spark workloads, and collaborates with stakeholders and technical teams. The role also includes mentoring engineers and establishing reusable engineering standards.

Design and build large-scale data pipelines, cloud migration strategies, and storage and processing solutions using Azure Synapse Analytics. Develop ETL/ELT pipelines, ingest terabytes or petabytes of data, optimize distributed systems, and create automation, monitoring, and administration tooling. Collaborate with cloud, infrastructure, engineering, DevOps, and customer teams to deliver production-grade healthcare data platforms.

Design, build, and optimize scalable data pipelines and Redshift data models; ingest from MySQL and real-time Kafka streams; migrate on-prem systems to AWS using Airflow, dbt, Lambda, Glue, and S3; embed data quality, observability, and security; collaborate with cross-functional teams to support mission-critical payments analytics.

Leads electrical protection and control systems for new-build data centre projects, covering design review, relay settings, coordination, arc flash studies, QA/QC, commissioning, documentation, and handover. Coordinates consultants, contractors, vendors, and stakeholders; validates designs against specifications and standards; oversees installation quality, defect closure, performance testing, and technical reporting.

Design, build, and support cloud-based data pipelines, data models, and enterprise data warehouse solutions. Partner with stakeholders on business initiatives, troubleshoot data and performance issues, lead projects, mentor developers, evaluate technologies, and drive automation and continuous improvement using GCP and related data engineering tools.

Lead the migration and modernization of enterprise SQL Server databases to public cloud platforms. Administer 24/7 SQL Server environments, implement high-availability and disaster-recovery solutions, tune performance, manage backups, patching, and upgrades, and automate infrastructure with PowerShell and Terraform. Support cloud security, provisioning, monitoring, incident resolution, and application stakeholder collaboration within Agile and DevOps environments.

Designs, builds, and supports cloud-based data pipelines, data models, warehouses, and integrations, primarily using GCP. Troubleshoots performance and technical issues, leads enterprise initiatives, mentors developers, evaluates data technologies, and drives automation and continuous improvement. The role partners with business analysts, architects, and stakeholders to deliver global data engineering projects.

Designs and executes data, ETL, business intelligence, and database testing. Validates end-to-end data flows using SQL and BigQuery within GCP, performs data quality checks, documents defects, and supports root-cause analysis. Collaborates with developers, analysts, and stakeholders to improve test automation, delivery governance, and testing efficiency. The role requires 5–7 years of quality engineering or data testing experience, with preferred knowledge of cloud platforms, Python, dbt, and DevOps.

Leads enterprise Oracle database migration and modernization to public cloud platforms. Administers Oracle 19c environments, Data Guard, ASM, backup and recovery, tuning, patching, upgrades, and high availability operations. Automates provisioning and lifecycle processes using Linux, shell scripting, and Python, while supporting cloud security, governance, monitoring, and incident resolution. Collaborates with application stakeholders and contributes to Agile delivery, documentation, and self-service database services.

Lead the migration and modernization of enterprise Oracle databases to public cloud platforms. Administer Oracle 19c environments, Data Guard, ASM, backup and recovery, tuning, patching, and upgrades in a 24/7 setting. Develop Linux, shell, and Python automation; support cloud security, governance, lifecycle management, monitoring, and self-service provisioning. Collaborate with application teams, resolve incidents and alerts, and maintain operational documentation using Agile and DevOps practices.

Lead migration and modernization of enterprise SQL Server databases to public cloud platforms. Administer mission-critical SQL Server environments, including Availability Groups and Distributed Availability Groups, while managing tuning, capacity planning, backup and recovery, patching, upgrades, monitoring, and production support. Automate infrastructure and database operations with PowerShell and Terraform, maintain cloud security standards, resolve critical incidents, and collaborate with application stakeholders in an Agile environment.

Design, build, and maintain enterprise ETL/ELT pipelines in Microsoft Fabric; ingest and transform data from diverse sources into dimensional star schemas; optimize performance and cost; implement data quality checks and monitoring; document architecture and pipelines; collaborate with analysts, stakeholders, and global engineering teams to deliver Power BI-ready analytics datasets.

Designs and maintains scalable data pipelines using AWS, Spark, Kafka, Airflow, and related technologies. Collaborates with product, data science, and business teams; develops reporting dashboards; documents data flows and runbooks; optimizes workflows; troubleshoots data processing issues; and supports Agile delivery and CI/CD practices.

As a Senior Data Engineer, you will develop and maintain data pipelines for healthcare data, ensuring data quality, reliability, and adherence to enterprise standards while collaborating with architects and stakeholders.

The Senior Data Engineer will develop data ingestion, transformation, and enrichment pipelines, ensuring data quality and reliability. Responsibilities include creating Bronze and Silver data layers, using SQL and dbt for implementation, and collaborating with architects and stakeholders to align data solutions with enterprise standards.

As an Azure Data Engineer, you will innovate and maintain data engineering services for Fortune clients, develop software for large projects, and utilize Azure components for solutions.

Build, optimize, and maintain scalable AWS-based data pipelines and data lakes (Snowflake/Databricks). Implement streaming ingestion (Kinesis/Kafka), CDC, automated data quality checks, and ML-ready feature stores. Collaborate with Product, ML, and Analytics teams, own pipeline QA, observability, and participate in on-call rotations to resolve production data issues.