• Designed and deployed an AI-driven analytics platform using Oracle 23ai Vector Search and Neo4j graph modeling to enable semantic querying and structured data exploration across supply chain datasets. • Engineered scalable data transformation and feature engineering pipelines in Python and SQL to support high-volume operational analytics and decision workflows. • Developed interactive real-time analytics dashboards to visualize GPS, battery, and sensor telemetry streams, improving data interpretability and enabling faster operational insights.

• Managed and analyzed 100K+ healthcare records across frontend and backend systems using SQL-based validation, reconciliation rules, and data quality checks, improving system stability by 95% and reducing production data defects. • Designed and automated end-to-end SQL transformation and validation pipelines, reducing manual processing effort by 25%, improving release accuracy, and strengthening data governance compliance across healthcare workflows. • Built executive-facing Excel and Tableau dashboards to track operational KPIs, defect trends, and release metrics, cutting reporting turnaround time by 30% and enabling faster data-driven decision-making for business stakeholders. • Led a cross-functional Agile/Scrum team of 5+ analysts and QA engineers, partnering with Product Owners to ensure 100% requirement coverage, authoring detailed test specifications and validation reports, and driving a 20% improvement in delivery alignment with business goals.

• Improved data transformation accuracy across integrated healthcare systems by performing complex SQL joins, aggregation checks, reconciliation logic, and schema audits on large relational datasets prior to production release. • Reduced manual validation effort by 10+ hours per week by developing reusable SQL verification scripts and backend automation frameworks for cross-system data consistency checks. • Strengthened end-to-end pipeline reliability by collaborating with engineers to debug ETL failures, analyze API payload discrepancies, and resolve data inconsistencies across interconnected applications.