ETL QA Engineer Databricks PySpark

Validate enterprise data pipelines with Databricks and PySpark as an ETL QA Engineer at Kumaran Systems. Apply AI-assisted testing expertise.

This ETL QA Engineer validates large-scale data pipelines and ensures data quality. The work centers on Databricks, PySpark, ETL/ELT concepts, and data warehousing. You will use GitHub, GitHub Copilot, and GitHub Actions/Runners for CI/CD pipelines. The position also includes prompt engineering, AI agents, and AI-powered knowledge bases.

Key Responsibilities:

• Validate large-scale data pipelines across enterprise data environments
• Perform data quality checks and reconciliation techniques
• Use Databricks notebooks, jobs, clusters, Delta Lake, and SQL
• Improve testing efficiency and coverage with AI-assisted tools
• Build and validate AI-powered knowledge bases

Requirements:

• Strong hands-on Databricks experience across core platform capabilities
• Expert PySpark skills in transformations, actions, windows, and optimization
• Understanding of ETL/ELT, warehousing, and dimensional data modeling
• Experience with GitHub, Copilot, and Actions/Runners
• Experience crafting prompts for coding, testing, and documentation

Bring Databricks, PySpark, data validation, and AI-assisted QA skills to Kumaran Systems’ transformation engineering practice.