Spring BootREST APIsKafkaQuartz SchedulerReact.jsPostgreSQLRedisRate Limiting
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Spring BootREST APIsKafkaQuartz SchedulerReact.js
Experience
Software Engineer at Lumber (2025-03 – 2026-04)
Implemented Redis-based rate limiting to enforce per-client API quotas before requests reach downstream payroll services — stopping excess calls at the edge.
Designed async event-driven pipelines using Kafka with retry mechanisms and Dead Letter Topic (DLT) handling for fault-tolerant recovery of failed payroll events.
Built batch processing architecture for payroll sync jobs — chunking large datasets and controlling dispatch cadence via Quartz Scheduler to never breach API throttle limits.
Integrated with third-party payroll REST APIs, handling edge cases like error recovery, transactional rollback prevention, and throttling via Kafka-based retry strategies.
Built and consumed webhook event listeners — routing incoming events by type to trigger create or update operations, enabling real-time data consistency without polling.
Optimized PostgreSQL query performance by analyzing execution plans and applying targeted indexing strategies on datasets exceeding 1M+ records in production.
Built full-stack features end-to-end using React.js, REST APIs, and PostgreSQL following clean layered architecture (Controller → Service → Repository).
