Designed and implemented an AI-based SQL optimization workflow to analyze and rewrite queries, reducing execution times from hours to minutes and significantly improving overall system throughput
Integrated an OCI Generative AI Agent into a performance monitoring platform using RAG-based architecture, enabling automated diagnosis, summarization, and resolution of performance issues via backend services and improving response time and system reliability
Engineered and integrated performance benchmarking systems into internal backend reporting pipelines to detect regressions in dependent services, improving early issue detection and cross-team system reliability in production environments
Developed and maintained 10+ backend-driven applications with custom user interfaces to simulate real-world database and system performance issues, enabling DBAs and developers to diagnose bottlenecks and optimize system behavior
Built and maintained backend data pipelines leveraging Oracle Database, S3 storage buckets, and a dashboard interface to process and visualize resource usage, optimizing distributed resource consumption and reducing cloud infrastructure costs by 25%
Led migration of training and testing environments from on-premises systems to an Oracle Database Cluster (Exadata) platform, enabling high-throughput, concurrent workloads for analyzing query inefficiencies and meeting SLA targets
Mentored interns in developing backend-driven demos using SQL and Java, reinforcing best practices in system design, query optimization, and handling performance under concurrent workloads
Analyzed production database performance metrics to diagnose system bottlenecks and implemented optimized solutions, reducing query execution times from hours to minutes and ensuring SLA compliance for customer-facing systems