Top Data Engineer Jobs in Mumbai

Design, develop, and maintain scalable Microsoft Fabric and Azure data solutions. Build Lakehouse, Data Warehouse, OneLake, ETL/ELT pipelines, data transformations, and integrations using Python, PySpark, SQL, and Fabric tools. Implement medallion architecture, optimize data models and workloads, establish data quality monitoring, and support CI/CD deployments. Collaborate with analytics and business teams to deliver enterprise-scale data platforms.

Design, build and maintain scalable batch and real-time data pipelines and data products on AWS to ingest security telemetry, enable analytics/ML, ensure data quality and observability, integrate with enterprise security tooling, and drive DevSecOps/automation for the Group Security Data Platform.

As a Data Engineer Intern, you will write efficient code, learn new technologies, collaborate with teams, and deliver data products to improve decision-making.

Build and maintain batch and streaming data pipelines across AWS, Azure, and GCP using Databricks, Spark, PySpark, SQL, and Delta Lake. Implement medallion architecture, CDC, SCD, data quality, governance, security, metadata, and lineage controls. Configure storage, orchestration, CI/CD, monitoring, troubleshooting, and performance optimization. Collaborate with architects, data scientists, engineers, analysts, and product teams while documenting pipelines, transformations, testing, and operational procedures.

Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Azure Data Factory, Databricks, PySpark, Python, and SQL. Transform large datasets, optimize data ingestion and queries, monitor pipeline performance, resolve data quality issues, support data modeling, document engineering standards, and contribute to cloud data infrastructure improvements. The role also involves collaboration with architects and senior engineers and requires familiarity with Azure Synapse, Delta Lake, governance, and security.

Design, build, and maintain scalable Azure-based data pipelines and systems (Databricks, Data Lake, Synapse, ADF). Collaborate with cross-functional teams, ensure data quality and integrity, optimize performance, monitor and troubleshoot systems, and stay current with industry trends to improve solutions.

Principal Data Engineer responsible for developing and supporting Databricks pipelines, integrating heterogeneous healthcare data sources, modeling unified data products, and ensuring data quality and availability. The role partners with business stakeholders, product teams, data engineers, and clinical leaders to gather requirements, create datasets, support ad hoc analytics, enable machine learning and AI use cases, and assist with acquisition integrations. Extensive healthcare data, cloud, SQL, PySpark, and Python experience is required.

Build and maintain scalable data products using Snowflake, dbt, and Airflow. Responsibilities include dimensional data modeling, SQL transformations, pipeline orchestration, data quality testing, exploratory analysis, SLA monitoring, documentation, and stakeholder requirement gathering. Partner with analytics, product, engineering, and business teams to deliver reliable, production-ready datasets while following software engineering, CI/CD, testing, and deployment practices.

Build and maintain enterprise data pipelines, ELT processes, data models, reporting structures, and analytics solutions. Cleanse, deduplicate, normalize, and govern data across warehouses and data lakes, including Snowflake. Develop dashboards and business intelligence models, ensure data quality and compliance, apply business logic, and collaborate with technical and non-technical stakeholders to deliver accurate insights and improve operational performance.

Looking for a Data Engineer lead to design and build scalable solutions, develop data pipelines, and support analytics and ML initiatives, while collaborating with cross-functional teams for quality data management.

Architect and optimize enterprise Power BI and Microsoft Fabric reporting solutions, semantic models, data pipelines, and governance. Develop interactive reports, integrate Fabric AI Agents, and enable self-service analytics. Manage Git-based CI/CD deployments across environments, enforce row- and object-level security, and automate data quality validation using Python, SemPy, PySpark, and Spark SQL. Build scalable data transformations and automate alerts for data anomalies.

Build and deploy Snowflake data warehouse solutions, develop Python-based ETL and ELT pipelines, design dimensional and star schemas, support data strategy and governance, and integrate operational data for analytics and reporting. Collaborate across development teams, participate in code reviews, troubleshoot complex data issues, and contribute within an Agile/Scrum environment.

Leads data engineering initiatives involving ETL/ELT pipelines, database optimization, orchestration, big data technologies, data modeling, BI performance, and data quality monitoring. Requires strong Scala, Python, SQL, and shell scripting skills, plus payments-domain expertise covering transaction processing, settlements, disputes, reconciliation, gateways, acquiring, issuing, and PCI-DSS compliance. The role also involves cross-functional communication, planning, facilitation, negotiation, and collaboration with senior stakeholders and clients.

Design, build, and optimize end-to-end data solutions using Microsoft Fabric, Azure Synapse, Databricks, Azure Data Factory, and Power BI. Develop scalable real-time and batch pipelines, data models, semantic and dimensional models, dashboards, reports, and self-service analytics. Apply medallion architecture, DataOps, monitoring, security, governance, quality controls, and performance tuning. Integrate Azure Machine Learning and streaming technologies when needed while delivering enterprise data and BI solutions for clients.

Lead and hands-on build cloud-native, microservice-based systems for the PitchBook platform. Drive architecture and design, implement testable scalable code, define non-functional requirements, mentor engineers, collaborate with architects and stakeholders, and deliver end-to-end initiatives while promoting engineering best practices and continual improvement.

Build and manage data connections, validate and normalize incoming portfolio files, automate monitoring and reporting, improve auto-reconciliation via data mining and transformations, support operations and development requests, and communicate technical solutions to non-technical stakeholders. Participate in light on-call duties.

Design, build, and maintain data connections and transformations, validate file deliveries, normalize external datasets, automate monitoring/reporting, improve auto-reconciliation, support operations and development, and communicate technical details to stakeholders.

Designs and maintains SAP-integrated ETL/ELT pipelines connecting ECC, S/4HANA, BW/4HANA, and cloud data platforms. Responsibilities include SAP data extraction, transformation, real-time integrations, dimensional modeling, database optimization, data quality monitoring, alerting, cost optimization, and documentation. The role partners with functional consultants, BI teams, FP&A stakeholders, and business leaders while developing cloud skills across AWS services such as Glue, Lambda, Airflow, and Redshift.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

Designs and supports data platform blueprints and components, collaborating with Integration and Data Architects to ensure cohesive system integration and data models. Monitors platform performance, recommends enhancements, supports data governance, and provides solutions across multiple teams. The role requires expertise in Alation Data Catalog, data integration, data modeling, and team leadership.

Designs and refines scalable data platform architectures using Cloudera Data Platform. Collaborates with Integration and Data Architects to ensure cohesive system and data-model integration. Leads platform performance and scalability improvements, troubleshoots complex issues, supports team decisions, mentors junior engineers, and provides solutions across multiple teams. Requires strong knowledge of distributed computing, big data, data integration, security, and governance.

Own the end-to-end real-time voice and data platforms, including AI agents for live calls, telephony and streaming integrations, call-data pipelines, analytics, dashboards, monitoring, and cloud infrastructure. Build AI workflows, product interfaces, and business automations; optimize latency, cost, reliability, and performance; respond to production issues; and mentor teammates while collaborating with product and domain experts.

Design, build, and maintain Azure-based data infrastructure and pipelines. Implement data models and schemas, ensure data quality, optimize distributed storage and processing (Databricks/PySpark), and establish engineering best practices while partnering with cross-functional teams.

Design cloud-native data and AI architectures, including data lakes, warehouses, ETL/ELT pipelines, real-time streaming systems, and infrastructure as code. Review architectural patterns, optimize performance and costs, align delivery with business objectives, support client presentations and workshops, and mentor junior team members. The role requires cloud solution design experience across AWS or Azure, knowledge of data and AI patterns, AI algorithm evaluation, communication skills, and an AWS Certified Solutions Architect Professional certification.

Designs cloud-native data and AI architectures, including data lakes, warehouses, ETL/ELT pipelines, real-time streaming, and infrastructure as code. The role evaluates cloud storage and processing options, optimizes performance and costs, guides architectural development, supports client workshops, aligns technical delivery with business objectives, and mentors junior team members. AWS or Azure expertise, AI algorithm experience, and AWS Certified Solutions Architect Professional certification are required.