Vinju Elizabeth Jose

Senior Qa Engineer @Prevalent AI

Architected BDD‑Cucumber automation suite (Python + Gherkin) that boosted API test coverage from 0 → 85 % and cut manual regression effort by ~40 %. Built CI/CD testing pipelines in Jenkins & ArgoCD; reduced deployment verification time from 30 min → 5 min per release. Designed PySpark data‑validation framework validating 5 TB+ of ingested data nightly, raising data‑quality SLA to 99.9 %. Mentored 4 junior QA engineers; instituted peer‑review process that halved escaped‑defect rate within two quarters. Received “Focused Award” (July 2021) for high‑impact project delivery and customer satisfaction. Spearheaded migration from manual to automated UI testing using Selenium, reducing UI regression cycle by 60 %. Led defect triage meetings with developers and product managers, improving resolution turnaround by 30 %. Integrated Apache Airflow DAG validations into test cycles, preventing 10+ production pipeline failures per quarter. Performed root cause analysis (RCA) for critical failures, contributing to improved platform stability and proactive test coverage. Authored 300+ detailed test cases and reusable scripts across modules, boosting team productivity and consistency. Collaborated with cross-functional Agile teams on sprint planning, estimation, and retrospectives to align QA goals with delivery timelines. Enabled early bug detection via shift-left testing strategy and story-level validations during grooming stages.