Sornadeepika Ponnan

Spearheaded end-to-end QA lifecycle validation across Web and Mobile (iOS/Android) platforms for a major retail e-commerce application, leading a 12-member cross-functional onshore/offshore team through daily defect triage, JIRA resource allocation, and strict release governance. Directed next-generation quality engineering for Google Shopping Agent AI by leveraging Gemini AI prompt engineering to simulate complex retail supply chains and warehouse fulfillment exceptions. Designed and optimized a highly scalable BDD hybrid automation framework using Cucumber, Java, and TestNG that expanded test coverage to 85% across 1,000+ critical retail workflows, while integrating Rest Assured API verification with third-party systems like Adeptmind Search and Mirakl. Orchestrated requirement grooming sessions with Product Owners, performed pre-production smoke testing for formal deployment sign-offs, and engineered Selenium Grid parallel processing architectures to reduce regression execution windows by 70% and slash production defect leakage by 40%

Architected and deployed scalable, BDD-style automation frameworks from scratch using Java, Selenium WebDriver, and Cucumber for large-scale healthcare (Medtronic) and media (Turner) applications, structuring over 800 automated test cases utilizing the Page Object Model (POM) design pattern to lower maintenance overhead by 45% and script duplication by 40%. Built robust automated API test suites using Rest Assured to validate complex JSON/XML payloads while executing backend SQL validation queries to ensure transaction data consistency. Successfully integrated automation runs into active CI/CD build pipelines, which slashed manual verification windows by up to 65% for major baseline software releases. Spearheaded defect control efforts by uncovering and logging over 200 critical workflow and data-integrity defects in JIRA, ultimately boosting live production environment stability by 40%

Engineered a scalable Java-based hybrid automation suite via Maven dependency frameworks to manage 700+ regression scripts for Lloyds Banking Group, while maintaining a legacy data-driven testing architecture using QTP/UFT to boost core regression test coverage to 75% for JPMorgan Chase. Configured optimized parallel execution flows via TestNG XML parameters that shortened environment validation windows by 65%, successfully decreasing execution times from 3.5 hours down to 1.2 hours. Implemented automated JDBC database connections to audit complex backend banking transactions across Accounts, Payments, and Loans modules. Identified and documented over 150 software flaws, intercepting 30+ high-severity environment blockers prior to production deployment to ultimately shrink post-release defect leakage rates by 35%.