Cloud Data Engineer

About the job : Cloud Data Engineer Experience: 5 8 Years Relevant Experience: Minimum 5+ Years Location: Bangalore Work Mode: Hybrid 3 Days a Week in Office Job Summary We are looking for an experienced Cloud Data Engineer with strong hands-on expertise in Hadoop, HDFS, Hive, and PySpark. The ideal candidate should have solid experience in big data processing, distributed computing, data transformation, and building scalable data pipelines. Key Responsibilities Design, develop, and maintain scalable data processing pipelines using PySpark. Work with Hadoop and HDFS for distributed data storage and processing. Develop, optimize, and maintain Hive queries, tables, and data models. Perform large-scale data extraction, transformation, and loading (ETL) using PySpark and Hadoop ecosystem technologies. Optimize Spark jobs and Hive queries for performance and resource utilization. Handle structured and semi-structured data for analytics and reporting requirements. Troubleshoot data pipeline failures, data quality issues, and performance bottlenecks. Collaborate with data engineers, analysts, and other stakeholders to deliver reliable data solutions. Follow best practices for data security, data quality, code maintenance, and performance optimization. Required Skills Hadoop: Strong hands-on experience with the Hadoop ecosystem. HDFS: Experience managing and processing data in the Hadoop Distributed File System. Hive: Proficiency in HiveQL, query optimization, and data management. PySpark: Strong hands-on experience in distributed data processing and transformation. Big Data: Good understanding of distributed computing and large-scale data processing. ETL/Data Pipelines: Experience developing, maintaining, and optimizing data pipelines. SQL: Strong query-writing and data manipulation skills. Troubleshooting: Ability to identify and resolve data processing and performance issues.