Backend Engineer(Hadoop)

. Design, develop, and maintain scalable backend applications and data processing services using Java/Spring Boot and related technologies.

. Develop and support distributed data processing solutions using the Hadoop ecosystem, including HDFS, Hive, Spark, and related components.

. Build REST APIs, backend services, and data integration components to support enterprise applications and data platforms.

. Develop efficient ETL/data processing pipelines and optimize large-volume data processing jobs.

. Work with Hadoop/Hive/Spark to ingest, transform, process, and analyze large datasets.

. Troubleshoot application, data processing, performance, and production issues across backend and Hadoop environments.

. Implement code quality, unit testing, logging, monitoring, and performance optimization practices.

. Collaborate with architects, data engineers, application teams, and business stakeholders to understand requirements and deliver solutions.

. Participate in deployment, release management, production support, and incident resolution activities.

. Ensure solutions follow enterprise security, coding, data governance, and technology standards.

Key Skills:

. Strong experience in Java, Spring Boot, REST APIs, and backend development.

. Hands-on experience with Hadoop ecosystem, particularly HDFS, Hive, Spark, and YARN.

. Good knowledge of SQL, data processing, ETL, and distributed computing.

. Experience with Kafka or other messaging technologies is an advantage.

. Exposure to Linux/Unix, Git, CI/CD, and cloud platforms is preferred.

. Strong troubleshooting, analytical, and problem-solving skills.

. Experience working in large-scale enterprise or banking environments is preferred.

. Typically 5-8 years of relevant backend development experience, with solid hands-on Hadoop experience.