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:

Solid 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.

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