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.