Java Bigdata Developer

Job Description

Key Responsibilities: Design, develop, and implement big data solutions using Apache Spark and Hadoop . Develop high-performance distributed applications using Java . Optimize and manage large-scale data processing workflows . Work with HDFS, Hive, HBase, and other Hadoop ecosystem components . Implement real-time and batch processing solutions using Spark Streaming . Troubleshoot and optimize Spark jobs for better performance and efficiency. Collaborate with data engineers, analysts, and business teams to meet project requirements. Ensure data security, reliability, and scalability across distributed systems. Write efficient SQL queries for data extraction and transformation. Participate in Agile development processes , including sprint planning, code reviews, and stand-ups. Required Skills & Expertise: Strong programming experience in Java (Python/Scala is a plus). Hands-on experience with Apache Spark & Hadoop ecosystem . Experience with Spark SQL, Spark Streaming, and Kafka . Proficiency in HDFS, Hive, HBase, and YARN . Experience with data ingestion frameworks and tools. Strong understanding of distributed computing and parallel processing . Knowledge of ETL processes and data pipeline development . Experience with performance tuning and optimization of Spark jobs . Familiarity with cloud platforms like AWS, Azure, or GCP is a plus. Strong problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications: Experience with NoSQL databases (Cassandra, MongoDB, etc.) . Knowledge of containerization (Docker, Kubernetes) . Understanding of CI/CD pipelines for big data applications.