Engineered PayPal’s Core Payout Engine using Java, Spring Boot, and PayPal’s Payouts SDK, enabling secure, scalable, and automated batch-wise payouts with real-time transaction tracking and intelligent error handling via RESTful APIs.
Built and optimized React.js (v18) and TypeScript front-end dashboards that empower business users to configure payout batches, monitor live transactions, and visualize reconciliation metrics.
Leveraged Spring WebFlux and CompletableFuture for asynchronous processing and parallel execution, improving transaction throughput and reducing latency. Developed Spring Batch modules for high-volume reconciliation of millions of records daily, featuring fault tolerance, checkpointing, and multi-threaded scalability.
Implemented robust fault-handling and retry mechanisms using Resilience4j (circuit breakers, rate limiters), ensuring continuous operation during API throttling or downtime.
Containerized microservices with Docker and deployed on Amazon EKS, adopting blue-green deployments and auto-scaling for zero-downtime releases. Integrated AWS SQS and Lambda for event-driven communication and automated failure recovery, cutting manual interventions by 60%.
Enhanced system security with JWT and OAuth 2.0, ensuring PCI DSS compliance and granular role-based access control. Used PostgreSQL and Hibernate/JPA for efficient data management, audit tracking, and optimized query performance.
Set up Prometheus and Grafana dashboards for real-time monitoring of API latency and batch throughput, achieving proactive issue detection. Deployed ELK Stack (Elasticsearch, Logstash, Kibana) for centralized logging and analytics, reducing debugging time by 40%.
Delivered 92%+ test coverage through JUnit 5, Mockito, and CI/CD pipelines (Jenkins), maintaining exceptional reliability across 25+ production releases.