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.
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ETL QA Engineer Databricks PySpark in Toronto employer: Kumaran Systems
Kumaran Systems is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the AI-Driven GenAI QA Automation Engineer role. Located in North America, we offer competitive benefits, continuous learning opportunities, and a commitment to employee growth, ensuring that our team members thrive in their careers while contributing to cutting-edge projects in a dynamic Agile environment.
