Student Manager University at Buffalo
Architected and deployed end-to-end Java Spring Boot microservices on AWS (EC2, S3, Lambda) to support scalable data ingestion, transformation, and reporting workflows for operational analytics exceeding 500K+ records. Designed and integrated RESTful APIs using Java and Spring Boot to expose backend data services, enabling seamless communication between operational dashboards, reporting tools, and downstream data consumers with 99.5% uptime. Built and maintained automated ETL pipelines using Spring Batch and Spring Scheduler to process transactional datasets (revenue, attendance, inventory, performance metrics), enabling near real-time KPI monitoring and reducing manual reporting effort by 40%. Implemented asynchronous event-driven workflows using Kafka and RabbitMQ to decouple data ingestion and processing services, improving system resilience, fault tolerance, and throughput for high-volume operational data. Optimized relational database schemas and SQL queries using Hibernate ORM, indexing, partitioning, and connection pooling strategies, improving query performance by 30% and supporting complex analytical workloads across PostgreSQL and MySQL. Deployed and managed containerized Java microservices on AWS Lambda and EC2 using Docker and Kubernetes, ensuring scalable, low-maintenance inference and processing services with automated CI/CD pipelines via Jenkins and GitHub Actions. Implemented robust logging, monitoring, alerting, and error-handling mechanisms using Prometheus and Spring AOP, ensuring pipeline reliability, fault tolerance, and data integrity across distributed workflows. Collaborated with cross-functional teams in Agile sprints, participating in code reviews, system design discussions, and sprint planning to deliver scalable, maintainable Java-based data-driven solutions aligned with business objectives.