Data Engineer III

Looking to take your Data Engineering career to the next level? JPMorgan Chase & Co., one of the world's largest and most respected financial institutions, is hiring Data Engineer III professionals in Bengaluru, Karnataka. If you have experience with Python, AWS, Spark/PySpark, SQL, Data Pipelines, and Cloud Data Engineering, this is an outstanding opportunity to work on enterprise-scale data platforms that power critical financial services used by millions of customers worldwide. Whether you're passionate about cloud-native architecture, real-time data processing, or building highly resilient data platforms, this opportunity provides excellent technical challenges, career growth, and attractive compensation. JPMorgan Chase & Co. is one of the world's largest financial institutions with operations in over 100 countries. Serving millions of consumers, businesses, governments, and institutional clients, the company is a global leader in investment banking, commercial banking, asset management, consumer banking, and financial technology. Its engineering teams build high-performance systems capable of processing enormous volumes of financial transactions every day while maintaining exceptional reliability, security, and compliance standards. Working at JPMorgan Chase gives engineers the opportunity to solve complex technical problems at a global scale while collaborating with some of the industry's best technology professionals.

Design scalable cloud-based data platforms. Build reliable data pipelines. Develop backend services and APIs. Build microservices supporting enterprise data workflows. Optimize large-scale data processing. Work with Spark and PySpark. Build cloud-native AWS solutions. Implement CI/CD pipelines. Maintain data quality and integrity. Support analytics and reporting platforms. Collaborate with global engineering teams. Improve performance, scalability, and resilience.

Programming: Python, SQL. Big Data Technologies: Spark, PySpark. Cloud: AWS, AWS Glue. Data Engineering: Data Pipelines, Data Lake, Data Warehouse, ETL, Distributed Computing. Data Tools: dbt, Glue, Trino, Airflow, AWS Step Functions. Backend Technologies: REST APIs, Microservices. DevOps: CI/CD, Infrastructure as Code, Agile, Automation. Preferred Skills: Docker, Kubernetes, Kafka, Spark Streaming, TypeScript, React, AWS Certifications.