Aug 2024 – Jul 2025 · 11 mos · Bengaluru · Hybrid

• Technical Highlights:
• Built and scaled backend microservices using Go, PostgreSQL, Redis, and SQS to support high-volume transaction workflows and internal dispute systems.
• Designed and deployed daily cron jobs for automated case validation and correction, significantly reducing manual effort and human errors.
• Integrated Celery task queues with internal finance APIs to automate fee debits for Arbitration and Pre-Arbitration stages, ensuring accurate billing.
• Developed a proof of concept for the decomposition of Razorpay's Dispute monolith into microservices using API-first design principles and Redis-based messaging queues.
• Set up background job pipelines to detect and auto-correct invalid or mismatched dispute fields, improving system data hygiene and auditability.
• Business Outcomes:
• Resolved a ₹85 lakh money loss bug in the first week by tracing inconsistencies in reconciliation logic and implementing a durable fix.
• Saved over ₹1 crore annually by automating fee debit operations, eliminating reliance on manual processes and reducing financial leakage.
• Reduced dispute resolution time and internal escalations through proactive validations, improving internal SLAs and operational efficiency

Jul 2022 – Aug 2024 · 2 yrs 1 mo

• Technical Highlights:
• Led backend ownership of key modules including Stocks, Logistics, and Retail, architecting scalable APIs and internal tools using Python, Django, Celery, and PostgreSQL.
• Integrated the Shipsy logistics platform from scratch, handling REST API integration, webhook processing, and delivery tracking updates.
• Reduced latency of the homepage stock check API by 20% using multi-threading, Redis caching, and SQL query optimization.
• Built automation pipelines for retail sheet uploads using Pandas, Celery, and Cerberus-based validation, enabling bulk processing and error tracking.
• Migrated the core backend from Django 2.1.7 to 2.2, refactoring legacy code and resolving package-level compatibility issues.
• Optimized backend performance by reducing redundant API calls and introducing batch DB operations like bulk_create() and prefetch_related.
• Business Outcomes:
• Achieved a 95% reduction in manual effort for retail operations by automating Excel-based workflows for internal teams.
• Contributed to a 30% increase in operational productivity through performance improvements, integrations, and process automation.
• Improved customer experience and delivery accuracy by streamlining logistics data flow and improving stock sync reliability.
• Received the top annual performance rating during the entire tenure, awarded to the top-performing engineers quarterly.

Jan 2022 – Jun 2022 · 5 mos

Jun 2020 – Sep 2021 · 1 yr 3 mos

Jul 2019 – Jun 2020 · 11 mos

Jun 2020 – Jun 2021 · 1 yr