We are seeking an experienced Lead Hadoop Data Engineer with strong expertise in Python, SQL, and On-Premise Data Platforms. The ideal candidate will lead the design, development, and optimization of scalable big data solutions, working closely with cross-functional teams to deliver high-quality data pipelines and analytics solutions.

Lead the design and development of scalable data pipelines using Hadoop ecosystem tools Develop and optimize ETL workflows using Python and SQL Work on on-premise big data environments, ensuring performance, reliability, and scalability Manage and process large datasets using tools like Hive, HDFS, Spark, and MapReduce Collaborate with data analysts, data scientists, and business teams to understand data requirements Ensure data quality, integrity, and governance across systems Troubleshoot performance issues and optimize data processing jobs Mentor junior data engineers and guide best practices Participate in architecture discussions and contribute to technical decision-making

6+ years of experience in Data Engineering / Big Data Strong hands-on experience with Hadoop ecosystem (HDFS, Hive, Spark, MapReduce) Proficiency in Python and SQL Experience working with on-premise data platforms Strong understanding of data warehousing concepts and ETL processes Experience in performance tuning and optimization Good knowledge of Linux/Unix environments Strong problem-solving and analytical skills