Saptarshi Chakraborty

Redesigned the client support feature set using data-backed insights and user feedback, increasing the overall efficiency of support by 50%. Implemented a Priority Queue to efficiently load available support personnel who log in and sort them based on priority. Engineered a system to randomly assign available chat support personnel to clients based on priority and ensure a maximum of 5 clients per support person. Utilised STOMP-based communication to establish a reliable and efficient messaging channel between chat participants. Tech Stack: Java, Spring Boot, Spring Web Socket, Rabbit MQ, Socket.js, HTML, CSS.

Engineered a Portal application for US government healthcare directors and hospital chains using Spring Boot, JPA, Spring Security, and MySQL that streamlined patient data management; led to a 45% reduction in patient data errors and a 30% increase in efficiency. Created an additional application for data retrieval and storage using Spring Boot, JPA, ELK, and an elastic DB. Built a Javalin application for taking SSL certificates via REST template calls and storing them in JVM using Keystore. Constructed a Node.js application with Express.js for constant read operations from MySQL DB to send data to a transaction application for reindexing purposes. Utilized Apache POI XSSF, Open CSV to generate Excel documents for transaction reports and iText PDF to create payment invoice templates. Automated critical operations in the main Spring application, including scheduling Excel/CSV documents, verifying 500k+ Providers’ NPI and DEA numbers, and optimizing provider data management, resulting in a 75% reduction in manual effort and significant performance improvements, including a 50% faster query performance and a 30% reduction in response time. Implemented Swagger in all Spring applications, resulting in a 50% reduction in API testing time and a 30% increase in API documentation accuracy for a team of 5 developers. Designed and implemented a CPU-intensive task to detect transaction anomalies and send critical alerts to US government officials via Spring Mail service. The task processed over 500,000 transactions per day with an average processing time of under 15 seconds, achieving a 99.9% detection rate within a 6-month period, improving the security and compliance of the transaction system. Developed API functionality for pagination, sorting, and filtering of large data sets, resulting in a 40% improvement in data retrieval performance and a 50% reduction in database query times. Deployed applications manually in the EC2 server and also using Jenkins. Tech Stack: Java, Mav