Top Data Engineer Jobs in Bangalore

Design and build scalable data pipelines and ETL processes from internal and external sources. Improve data architecture performance, security, and maintainability (dbt, singer-taps, reverse ETL). Collaborate with analysts and product teams to build AI agents and self-serve analytics platform; participate in code reviews and design discussions.

Design, build, and optimize Azure-based data pipelines and data warehousing solutions using Microsoft Fabric and Azure Data Factory. Write and tune SQL, manage cloud resources, ensure data governance and security, troubleshoot ETL/ELT workflows, and collaborate with stakeholders to deliver analytics-ready data.

Design, build, and optimize ETL/ELT data pipelines using Microsoft Fabric and Azure Data Factory. Implement data warehousing, write and tune complex SQL, manage Azure resources, ensure data governance and security, and collaborate with stakeholders to support analytics and reporting.

The Principal Data Engineer will lead the data engineering team, architecting solutions and driving complex data projects to enhance operational data quality and support business decisions.

The Data Engineer will optimize the elluminate® platform for clinical data through coding, ETL processes, and deliver client-focused solutions while ensuring compliance with industry standards.

Design, build, and maintain cloud-native data pipelines and ETL/ELT workflows for high-volume trade lifecycle data. Integrate DTCC sources (RTTM, Settlement Web) into a Unified Trade Record, process ISO 15022 messages, manage trade exception databases, optimize SQL Server performance, and ensure data quality, lineage, governance, and observability while collaborating with business stakeholders.

Design, build, and maintain data pipelines and BI solutions for Smart Factory initiatives. Support data modeling, ETL/OLAP processes, dashboards, ad-hoc analysis, documentation, and stakeholder collaboration to improve operations and decision-making.

Design, build, and optimize 2K's core data platform (Snowflake/Databricks, S3, Kafka/Kinesis). Enable self-service DaaS, scale streaming and Spark workloads, implement RBAC and interoperability (Iceberg), and provide technical leadership to ensure high-performance, secure, and cost-efficient distributed data systems.

Operate and automate scalable ETL/ELT pipelines, implement CI/CD and IaC for data assets, ensure data observability and quality, enforce security/compliance, and support data scientists and analysts to maintain highly available global data infrastructure.

Lead design and delivery of enterprise-scale cloud data platforms. Architect and optimize ETL/ELT pipelines using Microsoft Fabric, ADF, and PySpark; implement data warehousing, advanced SQL transformations, governance, security, monitoring, and cost-aware operations; mentor engineers, partner with stakeholders, and drive reusable frameworks and resiliency improvements.

Senior individual-contributor and hands-on technical leader building scalable data infrastructure and analytics for private markets. Architect and oversee data pipelines/platforms (Snowflake, SQL, Python), define engineering standards, champion data governance, drive AI/ML adoption, and manage data engineering delivery and a team while aligning technical solutions with business priorities.

Design, build, and maintain scalable ETL/ELT pipelines in GCP (BigQuery, Dataform, Airflow) to integrate data from systems (Salesforce, NetSuite, APIs), build AI agents to automate finance workflows, support production month-end jobs in PST, manage IaC with Terraform, maintain CI/CD in GitLab, and produce documentation and BI/ML support for finance stakeholders.

Build production-ready ETL/ELT data pipelines, expand CI/CD for data workflows, integrate AI/automation, ingest data from varied sources, implement validation/monitoring, collaborate with product and analytics stakeholders, and design data architectures using cloud services and big data frameworks.

Design, develop, and maintain data solutions and ETL pipelines for high-throughput, payments-related systems. Perform data migration, extraction, mapping, reconciliation, and validation while ensuring no disruption to live payment processing. Mentor junior engineers, collaborate across teams, and act as SME for DB2 on mainframe environments.

Design, implement, and maintain ETL/ELT pipelines (DBT, Alteryx, AWS, Snowflake). Ingest and transform structured and unstructured data, enforce data security and governance, optimize data models and pipelines, and collaborate with stakeholders to support data scientists and visualization teams.

Design, build, and operate scalable data pipelines, storage, and APIs for a cloud-native data lake. Support analytics and AI workloads using Spark, Kafka, ClickHouse, and OpenSearch; implement monitoring, CI/CD, and performance optimizations while partnering with data scientists and product teams.

Design, build, and maintain scalable data pipelines and integrations for cloud and on-prem databases. Ensure data availability, quality, and observability; participate in SDLC, collaborate cross-functionally, and support automation and real-time/streaming use cases.

Design, develop, and maintain data pipelines and ETL processes using Databricks. Ensure data quality, collaborate with cross-functional teams, mentor juniors, and provide SME-level solutions and architecture decisions.

Design, develop, and maintain data solutions and ETL pipelines using Databricks. Ensure data quality, integrate and migrate data across systems, collaborate with cross-functional teams, mentor juniors, and drive team decisions while continuously improving data processes and architecture.

Design, develop, and maintain data solutions and ETL pipelines on AWS BigData. Ensure data quality, monitor and troubleshoot pipelines, document workflows, collaborate with cross-functional teams, and mentor junior engineers to deliver scalable data processing and migration solutions.

Design, develop, and maintain data solutions for data generation, collection, and processing; create pipelines, ensure data quality, and implement ETL processes.

Design, develop, and maintain data solutions and ETL pipelines; ensure data quality; build and deploy Databricks-based data platforms; apply Generative and Agentic AI and prompt engineering to deliver AI-driven enterprise solutions.

Design, build, and optimize telematic data pipelines and architectures using SQL and AWS. Assemble large datasets, automate processes, support analytics and cross-functional teams, and improve data delivery, scalability, and operational insights.

Design, develop, and maintain data solutions and ETL pipelines. Ensure data quality, optimize data workflows, collaborate with cross-functional teams, and resolve data-related challenges to deliver reliable data solutions.

Design, build, and maintain end-to-end ETL pipelines to migrate and transform data from on-prem systems to AWS using Glue (PySpark), Step Functions, Lambda, and related services. Ensure data quality, incremental loads, monitoring, cost optimization, and collaborate with solution and DevOps teams for testing and deployment.