Mar 2024 – Present · 2 yrs 3 mos · Bengaluru, Karnataka, India · Hybrid

• At Goldman Sachs, I worked on building scalable data and automation platforms across financial workflows, focusing on digitization, normalization, and reconciliation.
• Led development of key components for an invoice digitization platform processing 50K+ invoices per cycle across 750+ templates.
• Built and enhanced ~50% of platform APIs, improving OCR–LLM–datastore integration and increasing extraction accuracy to ~90%.
• Designed BPMN workflows, automated job orchestration, and developed Java-based parsers for complex invoice formats.
• Strengthened exception handling and data validation, improving downstream data consistency and audit traceability.
• Delivered measurable impact: reduced payment cycle from 30 to 7 days, saved $350K annually, and reduced dependency on 5+ FTEs.
• Additionally, contributed to an EQD Trade Normalization platform:
• Built a configuration-driven pipeline to standardize broker Excel/CSV trade files into a unified internal schema.
• Designed provider-level configurations for mapping, transformations, and validations, reducing onboarding effort for new formats.
• Developed ingestion and normalization workflows for multi-header datasets, publishing outputs to the data lakehouse.
• Implemented reconciliation logic to compare broker vs internal data and categorize exceptions, improving traceability and reducing manual investigation.
• Overall, improved data consistency across external feeds and enabled faster, more reliable downstream reporting.