Job Description
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 robust 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.

📌 Cloud Data Engineer (India)
🏢 SWITS DIGITAL Private
📍 India