Part of the Matchmaking engineering team
Our job is to find the best-suited partner that can serve a customer's request. It involves calculating complex predictive metrics using multiple signals around partner availability, skills, current inventory, preferences, location, historical behaviour, and other parameters. We need to make constant trade-offs between partner economics, marketplace economics, and customer delight while maintaining the overall fairness of the system.
- Implemented a workflow to sync matchmaking configuration files between local storage & google drive which helped the product managers & business folks to cut all their manual efforts by 60%
- Built dashboards for visualising & comparing matchmaking configuration files thereby improving the overall transparency of the matchmaking process
- Worked on the end-to-end deprecation of matchmaking's monolith & migration to microservices. This reduced the overall response time by more than 50%. Was responsible for redesigning, migrating, and platforming many fulfillment use cases. Migrated 46 APIs, 12 Kafka events & backfilled 8 database collections. This drastically helped to reduce the tech debt. It also improved the overall system performance since the new system scaled well during peak times