Top Data Engineer Jobs in Bengaluru

Develop, optimize, and maintain Python/PySpark data applications and ETL pipelines; write SQL; manage data files and orchestration (Airflow); collaborate across teams to design, deploy, and troubleshoot data solutions while following DevOps and cloud (AWS) practices.

Design, develop, and maintain Microsoft Customer Data Platform (CDP) solutions using Azure. Build and optimize data pipelines, integrate multiple data sources (Dynamics 365, Dataverse), create customer profiles and segments, ensure data governance and security, monitor CDP performance, and provide technical support for CDP implementations.

Design, build, and maintain ETL/data integration pipelines and complex SQL queries. Support reporting and BI tools (PowerBI, Tableau, MicroStrategy). Work with Python and cloud infrastructure; AWS Airflow/Glue and Java/Scala experience preferred. Analyze data requirements, troubleshoot issues, and contribute to data product development. Requires initiative, problem-solving, and relevant engineering degree.

Senior Azure Data Engineer responsible for designing and implementing end-to-end data pipelines using Azure Databricks, Azure Data Factory, and PySpark. Work with Delta Lake, Spark SQL, and data warehousing concepts to build scalable ETL/ELT solutions; collaborate on analytics and Power BI integration. Availability for 2pm-11pm/12am IST shift required.

Data Engineer responsible for building and maintaining ETL pipelines, data processing workflows, and data platforms. Must have strong hands-on experience with Healthcare Revenue Cycle Management and understanding of healthcare data workflows. Role requires hybrid (onsite + offshore) work and immediate availability.

Develop ETL pipelines and data transformations for analytical reports. Responsibilities include data ingestion, transformation, troubleshooting, and ensuring data structures for reporting support.

Design, build, and maintain scalable ETL/ELT pipelines and microservices for marketing and product data, ingesting from ad platforms (especially Meta Ads) and event systems. Enable campaign performance tracking, lead funnel analysis, attribution, and revenue reporting. Ensure data quality, observability, governance, and documentation while collaborating with marketing, growth, and analytics to deliver actionable datasets and drive business outcomes.

Build and maintain scalable ETL pipelines on GCP, transform large/disconnected datasets, automate and optimize data delivery, support stakeholders, and apply data engineering best practices including testing and release management.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Design, build, and optimize Snowflake data models and dbt pipelines. Create Power BI reports and paginated RDLs with DAX and row-level security. Manage CI/CD with Azure DevOps, version control with Git, enforce data quality and governance, and optimize warehouse cost and performance while collaborating with business stakeholders.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

Design, build, and maintain scalable data pipelines and infrastructure while optimizing data systems. Collaborate with teams to ensure data reliability and compliance, and document internal standards.

This role involves developing and optimizing data solutions using PySpark and Informatica BDM while collaborating with various teams on Risk & Compliance platforms.

As a Data Engineer, you'll optimize data workflows, design robust data solutions, and collaborate with teams to support data-driven initiatives.

Design, build, and maintain ETL/ELT pipelines ingesting high-volume advertising data into Snowflake; develop Snowflake stored procedures and data models; manage AWS Lambda (Node.js/Java), S3 data lake, and SQS workflows; monitor data quality and pipeline health; implement alerting; document schemas and collaborate on DSP integrations and attribution features to support analytics and Cool AI.

Design, build, and optimize scalable Azure-based data pipelines and SQL data models to support sales and inventory analytics. Implement PySpark data transformations, data quality checks, monitoring, and Power BI backend optimizations while integrating ERP and external data sources and supporting deployments and governance.

The Senior Data Engineer will design and optimize scalable data pipelines, implement real-time streaming pipelines, collaborate with data scientists, and oversee CI/CD and data quality practices.

Design, develop, and optimize distributed PySpark data pipelines using the Apache ecosystem (Hadoop, Hive, HDFS). Build scalable ETL workflows, implement data quality checks and lineage, integrate structured and unstructured sources, collaborate with data scientists and stakeholders, tune performance, and maintain code in Python/Java with version control and CI/CD.

Design and implement Lakehouse architecture with OneLake and Fabric, build medallion Delta table layers, migrate on‑prem SQL Server/SSIS to Fabric pipelines and notebooks, reverse‑engineer and document complex SQL logic, produce data mappings and dependency docs, and collaborate with functional teams to support migration and simplification of legacy logic.

Design, build, and maintain scalable AWS-based big data pipelines and ETL workflows using Spark/Hadoop. Collaborate with engineers and analysts to optimize data storage, ensure data quality/security, troubleshoot ingestion and transformation issues, and implement data lake and warehousing solutions.

Develop and maintain Python- and SQL-based analytics, reports, dashboards, and RESTful APIs. Collaborate with Product Management and Professional Services to gather requirements, estimate projects, ensure data accuracy, optimize queries, and deliver customer-facing analytics solutions. Master data models and data warehouse architectures and generalize custom reports where possible.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

The Data Quality Engineer will design and implement a data quality framework in Databricks, focusing on automated profiling, quality rule execution, cleansing, and reporting, while improving data accuracy and trust across datasets.

Zinier seeks a hands-on Senior Data Engineer to design and build a medallion data architecture on AWS, focusing on data governance, ETL pipelines, and AI/ML readiness while collaborating across teams.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.