
QA Engineer
2 weeks ago
Key Responsibilities
Design and execute test plans, test cases, and test scripts for data pipelines in Databricks.
Validate data ingestion, transformation, and processing workflows (Delta Lake, Spark jobs,
ML pipelines).
Perform functional, integration, regression, and performance testing for data applications.
Conduct data quality checks using SQL, Python, and Databricks notebooks.
Use AI-powered QA tools (e.g., Testim, Mabl, Applitools, or GitHub Copilot/Cursor) to:
Auto-generate test scripts.
Enhance test coverage and reduce manual effort.
Detect anomalies and patterns in test results.
Collaborate with developers and data engineers to troubleshoot and resolve defects.
Implement CI/CD-enabled automated testing for data workflows.
Monitor and report defects, metrics, and quality trends using test management tools.
Ensure compliance with data governance and security best practices.
Required Skills & Qualifications
4–6 years of experience in QA/Software Testing.
Hands-on experience in Databricks (Delta Lake, Notebooks, Jobs, Workflows).
Strong in SQL, Python, and data validation techniques.
Experience testing ETL pipelines, big data systems, or data lakes.
Knowledge of automation frameworks (PyTest, Robot Framework, or similar).
Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps).
Strong understanding of data quality, data governance, and test automation practices.
Preferred Skills
Exposure to Snowflake, Databricks, or other data warehouses.
Familiarity with Spark performance testing.
Experience with Agile/Scrum methodologies and Jira/Confluence.
Job Type: Contractual / Temporary
Contract length: 6 months
Pay: ₹300, ₹600,000.00 per year
Work Location: Remote
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