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: Robust 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.

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📌 ETL QA Engineer Databricks PySpark (Ontario)
🏢 Kumaran Systems
📍 Ontario