Data Tester

Key Responsibilities:

• Design, develop, and execute test cases to validate data ingestion from source systems (SQL, APIs) to Databricks UAP platform.
• Perform schema validation, data completeness, transformation, and row-level data checks between source and target.
• Utilize SQL extensively for data profiling and validation.
• Leverage PySpark and Pandas for large-scale data comparison and automation.
• Maintain and enhance the Data Test Automation Framework using Python/PySpark for efficient and scalable data testing.
• Participate in daily stand-ups, sprint planning, and retrospectives following Agile practices.
• Manage and track test progress, issues, and risks in JIRA.
• Ensure adherence to QA documentation practices:
• Test Plan
• Test Scenarios & Test Cases
• Test Summary Reports
• Defect Reports
• Own and drive the Defect Life Cycle, working closely with developers and product teams to ensure timely resolution.
• Collaborate with business analysts and developers to understand data requirements and ensure high test coverage.

Required Skills:

• 4+ years of experience in QA/testing with a strong focus on data validation.
• Strong proficiency in SQL (Joins, Subqueries, Aggregations, Data Profiling)
• Experience in testing data pipelines ingesting from SQL and APIs to Databricks.
• Hands-on with Python and Pandas for data manipulation.
• Working knowledge of PySpark and familiarity with Spark DataFrames, transformations, and data handling.
• Knowledge of Agile testing processes and QA best practices.
• Familiar with QA documentation and reporting standards.
• Experience with JIRA for test and defect management.
• Good understanding of Defect Life Cycle and its role in maintaining software quality.