Hyderabad, Telangana, India
• Boosted trading app search speed by 70% by reducing DAO/API calls and optimizing memory usage, delivering faster results for users.
• Cut initial load times by 50% for allocator and trading screens by utilizing caching and reusing DBDTO objects.
• Enhanced manager notification system by displaying external fund names, adding pre-alerts, and sync process to ensure compliance accuracy
• Built an exception management tool that automates 25% of resolutions, auto-detects resolved exceptions, and allows skipping with audit trails for direct data upload.
• Optimized an existing API by implementing batching and parallelization, achieving a 10x (900%+) speedup for upserts in MongoDB.
• Reduced batch job processing time from over 100 days to 1 day by combining API optimization with advanced filters, listeners and parallelization processing for ingesting 12 million+ funds into data lake.
• Optimized MongoDB lock management during upserts, resulting in a performance improvement of over 10%.
• Enhanced memo generation microservice with section-wise refresh, page anchors, and audit history, eliminating 1000+ manual memos/year more while ensuring strong data consistency.