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Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end data quality validation for large scale Databricks batch pipelines across Bronze, Silver, and Gold layers.
Design, develop, and maintain scalable automated data validation frameworks using PySpark, Python, and Databricks SQL.
Manage test case execution and defect tracking using tools like Xray and Jira, ensuring data correctness and release readiness.
Minimum Requirements
4+ years of experience in Software Quality Assurance or Data Quality Engineering for enterprise data platforms.
Strong hands-on skills with Databricks SQL, Python, PySpark, and data validation techniques in Medallion architecture.
Bachelor’s degree in Computer Science, IT, Engineering, or related field.
Experience working with Agile/Scrum methodologies and test management/defect tracking tools (Xray, Jira).
Ideal Candidate Profile
Proven expertise in building automated data validation frameworks on Databricks and Delta Lake environments.
Experience implementing integration, regression, and end-to-end testing strategies with an automation-first approach.
Familiarity with AI concepts and applying AI tools to optimize workflows and enforce responsible AI practices in data platforms.