Datumsure
Head of Quality | December 2023 - October 2026
Datumsure
Head of Quality | December 2023 - October 2026
Served as the company's sole QA professional, first on doTERRA and then owning quality for Tapestry after the client project ended.
- Promoted shared quality practices through recurring reviews with Tapestry team representatives before joining the product.
doTERRA - Client project
NestJS and Next.js wellness platform using connected health data to inform recommendations for products, healthy habits, and exercise.
- Coordinated the development team, acted as the client liaison, and translated requirements into functional tasks within technical constraints.
- Built a Playwright end-to-end test automation framework and integrated it into GitLab CI/CD to run after deployments to lower environments.
- Built a configurable k6 framework measuring request latency, payload metrics, and p50, p90, and p99 percentiles, extending an existing JMeter process assessed through database-record counts.
- Owned manual production deployments over SSH to the client's on-premises servers, coordinating release tasks with other teams.
Tapestry - Internal product
Datumsure platform integrating databases from multiple sources and providing users with AI-powered data analysis.
- Defined the quality strategy and negotiated feature scope with the product lead.
- Built a BehaveX and Python automation framework, expanding validation beyond sprint demos of feature happy paths to less common scenarios.
- Introduced Gherkin so managers could understand test coverage and interpret passing and failing results.
- Co-designed a system with DevOps to deploy test environments, execute tests, and expose service status, basic metrics, and logs without requiring access to the AWS console.
- Containerized testing frameworks, persisted reports in volumes, and removed runners after execution to optimize resource usage.
- Built a Locust performance testing framework to assess how new features affected application performance.
- Validated client-data access policies and helped define improvements to policy storage and enforcement, including redaction of restricted data before exposure to a large language model (LLM).