thrill-labs - Quality Engineering Lead

• Own the quality of released functionality end-to-end across multiple product areas • Join product discovery and specification work early to identify ambiguity, missing edge cases, inconsistent behavior, and quality risks before development starts • Review, create (if necessary), and maintain acceptance test cases for new features and changes • Build and maintain regression test packs for manual execution • Perform structured manual verification before release, together with Product Managers and Engineers • Define feature release readiness criteria and provide a clear quality sign-off or risk assessment before the release • Maintain a centralized view of test coverage across frontend and backend, including what is automated, what is not, where the gaps are, and what should be prioritized next • Work with Engineering Managers and engineers to reduce blind spots in automation coverage • Contribute directly to Playwright-based test coverage where useful, and be comfortable reviewing existing automated tests • Read and understand backend tests written in Java and identify missing quality coverage in backend-heavy features • Help define a practical, risk-based test strategy for different types of product changes • Track defects by feature and product area, identify trends, and report on recurring quality risks • Analyze escaped defects and production issues, then turn the findings into better specifications, stronger regressions, and improved automation priorities • Drive automated data reconciliation workflows to verify that data in product services and the data warehouse remains consistent • Define and maintain data quality checks that go beyond row counts, including field-level diffing, decimal precision validation, currency/value consistency, and referential integrity checks • Help implement automated quality gates that detect schema drift and backend changes that could break warehouse ingestion before code is merged • Partner with backend engineers and the data warehouse engineer to identify high-risk data models and pipeline changes, and ensure they are covered by appropriate checks • Create a clear view of current automation coverage and blind spots • Establish a lightweight but reliable release quality process • Improve the quality of feature acceptance criteria before implementation starts • Reduce avoidable regressions and repeated issue categories • Give Product Managers and Engineering Managers better visibility into release risk • Help teams focus automation effort on the highest-value gaps • Introduce practical controls that detect data mismatches and schema drift before they affect production or reporting • HOW WE WORK WITH THIS ROLE • This role does not replace the engineer's ownership of quality. Engineers remain responsible for the quality of their code and automated tests. The data warehouse engineer remains responsible for building and maintaining warehouse ingestion and models. • This role provides independent quality ownership across the release lifecycle: improving specifications, defining coverage, driving visibility, validating readiness, and ensuring product and data integrity over time.