• Designed and built a scalable shipment tracking system using Node.js, enabling 3,000+ customers to track 1M+ container shipments in real‑time across global ports.
• Designed and implemented event‑driven distributed shipment tracking data aggregation service, leveraging Azure service bus queues and Kubernetes to ensure fault tolerance and high availability.
• Developed REST APIs for shipment tracking, including shipment exceptions, event notifications, and geolocation tracking, integrating with Google Maps API. Experienced in RBAC and access control policies.
• Worked on performance optimizations and reduced API response times (from 5s to <1s in some cases) through caching, query indexing, Redis and ElasticSearch‑based enhancements, improving system’s scalability and efficiency.
• Helped on the migration of a multi‑tenant Kubernetes cluster to multiple single‑tenant clusters, improving fault tolerance, security, and scalability.
• Developed and launched a pluggable feedback service, a reusable service with a UI component that integrates into shipment tracking application, enabling user feedback collection across different modules.
• Took the initiative in establishing on‑call playbooks, reducing support time by 60+ minutes per incident and improving on‑boarding efficiency for 20+ customers and these were adopted by 10+ team members to streamline onboarding and support.
• Mentored and guided junior engineers in distributed systems design, microservices architecture, conducting code reviews and architectural deep dives.
• Technologies: Node.js, Java, REST API, Redis, Azure Kubernetes, Unit Testing, Distributed Systems.
