Role Summary Act as a critical quality gate between development and deployment for data products, pipelines, and analytics solutions.Ensure products are production-ready, functionally sound, and trustworthy at scale. Collaborate directly with Analytics Engineers, Data Engineers, and product stakeholders. Key Responsibilities Analytics Product Validation: Ensure data surfaces correctly reflect underlying data, handle edge cases, and maintain long-term accuracy. Develop deep functional knowledge of metrics and data sources to create meaningful test cases. User Acceptance Testing (UAT): Execute end-to-end UAT for analytics dashboards and pipeline-driven features before deployment. Translate business requirements and acceptance criteria into structured test plans, cases, and scripts. Partner with stakeholders to validate that features meet business intent. Document and track defects, edge cases, and regression issues. UI Testing & Interaction Validation: Build and maintain automated UI test suites (e.g., using mabl) to validate navigation, filters, chart rendering, and responsive behavior. Manage test environment configuration and baseline visual snapshots. Triage failures surfacing in CI/CD pipelines. Data Validation & Pipeline Correctness: Perform functional testing of data transformation logic, dbt models, SQL pipelines, and BI outputs. Validate data quality (completeness, accuracy, consistency, and referential integrity) Assist in code reviews for SQL/dbt changes to ensure adherence to team standards and correctness Automated Test Script Development: Develop automated testing as a primary work product using tools like Python/pytest for backend/data validation, mabl for UI, and Postman/Newman for API testing. Version-control all scripts and ensure documentation allows for team maintainability. Regression Testing: Design and maintain the regression testing infrastructure to ensure safe release deployments. Manage data fixtures and expand coverage as new features ship. Defect Analysis & Reporting: Write clear,reproducible bug reports detailing inputs, expected vs. actual outputs, and environment data states. Triage issues and communicate severity clearly to product and engineering leads