Java Full Stack Developer
- Engineered high-performance Java 11 backend using Spring Boot 2.7, implementing CompletableFuture, Java Streams, and Optional for concurrent transaction processing in core banking systems, improving transaction throughput by 25%.- Designed microservices architecture with Spring Cloud Netflix Eureka, Hystrix, Ribbon, and Spring Cloud Config for centralized configuration management of distributed banking services.- Implemented reactive programming using Spring WebFlux and Project… Show more - Engineered high-performance Java 11 backend using Spring Boot 2.7, implementing CompletableFuture, Java Streams, and Optional for concurrent transaction processing in core banking systems, improving transaction throughput by 25%.- Designed microservices architecture with Spring Cloud Netflix Eureka, Hystrix, Ribbon, and Spring Cloud Config for centralized configuration management of distributed banking services.- Implemented reactive programming using Spring WebFlux and Project Reactor for non-blocking I/O in high-throughput financial transaction scenarios, reducing response times by 40% under peak loads.- Developed security layer using Spring Security, OAuth2, JWT, and JAAS for multi-factor authentication, integrating LDAP and Active Directory for employee access control.- Utilized Spring Integration for external payment gateway connections, implementing JMS with Apache ActiveMQ Artemis for reliable inter-service messaging.- Optimized Oracle SQL, DB2, and Vertica databases using advanced indexing, partitioning, and materialized views to enhance the performance of analytical queries on historical transaction data, reducing query execution time by 30%.- Integrated Apache Kafka, Spring Kafka, and Kafka Streams for real-time event processing and complex event streaming in fraud detection and transaction monitoring.- Developed responsive Single Page Applications using Angular 10, Angular CLI, and Ivy compiler for optimized customer-facing banking portals, decreasing page load times by 20%.- Implemented data manipulation and analysis using Python libraries such as NumPy, Pandas, and Matplotlib.- Configured ELK stack with Elasticsearch, Logstash, Kibana, Filebeat, and Metricbeat for comprehensive logging and monitoring, integrating Prometheus and Grafana for metrics visualization, improving system observability and reducing mean time to resolution by 35%. Show less