QA Engineer – Data Platforms

Key Responsibilities:

• Define and execute comprehensive test plans, test cases, and regression suites for batch and real-time data pipelines in Databricks and related tooling that support audience, personalization, and measurement use cases.
• Validate data models, feature/attribute pipelines, and marketing data feeds to decisioning systems and measurement platforms for accuracy, completeness, and consistency.
• Design and implement data-quality validation frameworks, automated test scripts, and monitoring checks so segments, flags, and attributes are accurate and trustworthy.
• Verify governed customer attributes and audiences delivered to activation platforms (e.g., Hightouch, Salesforce Marketing Cloud) against requirements, with clear defect documentation and traceability.
• Partner with data science and engineering to validate productionized model features and architecture changes, ensuring alignment on data contracts and identity resolution.
• Assess and enforce privacy and compliance requirements across all data flows through targeted test coverage.
• Provide leadership-ready quality status, defect trends, risk assessments, and metrics reporting, and prepare decision memos that drive cross-team and leadership alignment.

Basic Qualifications:

• 5+ years of experience in a quality assurance or quality engineering role, preferably in data-intensive or marketing technology environments required.
• Hands-on experience testing data pipelines, ETL/ELT processes, and data platforms (e.g., Databricks, Snowflake, or similar) strongly preferred.
• Strong SQL skills for data validation and exploratory testing preferred.
• Experience with test automation tools and frameworks (e.g., pytest, Selenium, or equivalent).
• Familiarity with CI/CD pipelines and integrating quality gates into release workflows.
• Experience with defect tracking and test management tools (e.g., Jira, TestRail, or similar).
• Solid understanding of data quality dimensions (accuracy, completeness, timeliness, consistency) and how to measure them.