Sep 2022 – Present · 3 yrs 9 mos

• Lead SDET at S&P Global with 6+ years of experience in data pipeline testing, Python automation, and AI/ML engineering. I own end-to-end data quality validation across Databricks, Kafka, NiFi, and Elasticsearch for large-scale financial data platforms.
• Key highlights:
• ✅ Built Python automation framework (CAFE) — cut manual validation effort by 60%
• ✅ Developed ML classification model — 80% accuracy for client data matching
• ✅ Deployed AI agents using Claude Sonnet, Gemini & GPT-4 for internal smart search
• ✅ Integrated CI/CD test automation reducing post-release defects by 40%
• ✅ Won S&P Global Automation Contest 2021
• Passionate about the intersection of AI, data engineering, and quality automation.
• At S&P Global, I lead end-to-end test automation and data quality validation across complex data engineering ecosystems: Databricks, Apache Kafka, NiFi, and Elasticsearch. Every day, the pipelines I help validate process terabytes of financial data that global markets depend on.
• Over the years, I've pushed well beyond traditional QA:
• 🤖 AI & ML Engineering
• Built a production ML classification model in Python/Scikit-learn to match newly onboarded client data to existing company records — achieving 80% accuracy across the full ML lifecycle: EDA, feature engineering, model training, cross-validation, and batch deployment.
• Designed and deployed LLM-powered AI agents (Claude Sonnet, Gemini, GPT-4) on our internal platform to supercharge ProSearch — enabling natural language queries, semantic retrieval, and intelligent summaries for internal users.
• ⚙️ Automation & Frameworks
• Architected the CAFE Python validation framework — reducing manual testing effort by 60% and compressing full regression cycles to cycles to under 30 minutes. Integrated CI/CD pipelines in Jenkins that cut post-release defect leakage by 40%.

May 2019 – Present · 7 yrs 1 mo

• Worked as a senior SDET on data pipeline projects for end-to-end testing and automation of pipeline. Mode solutions and scripts to test data efficiently and easily. Worked on Data Bricks, MSSQL DB , NiFi Workflows and tested end to end dataflow. Developed automation test suites using python and inhouse framework. Used the Jenkins to execute the test suites in CI/CD Working under SAFE methodology.

May 2019 – Sep 2022 · 3 yrs 4 mos

• Presently working in Marketing Technology Team on Comparting and Fixed Income dataset. Our job include working in the Agile sprint where task is related to data warehouse change and incorporating new enhancements. We automate these test cases by using in-house framework developed in python and involve in creating methods to enhance its capability.