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 environmentsPerform data quality checks and reconciliation techniquesUse Databricks notebooks, jobs, clusters, Delta Lake,
and SQLImprove testing efficiency and coverage with AI-assisted toolsBuild and validate AI-powered knowledge basesRequirements:
Solid hands-on Databricks experience across core platform capabilitiesExpert PySpark skills in transformations, actions, windows, and optimizationUnderstanding of ETL/ELT, warehousing, and dimensional data modelingExperience with GitHub, Copilot, and Actions/RunnersExperience crafting prompts for coding, testing, and documentationBring Databricks, PySpark, data validation, and AI-assisted QA skills to Kumaran Systems’ transformation engineering practice.
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