Jun 2023 – May 2025 · 1 yr 11 mos

• Led the redesign of the TITAN framework, replacing Fundware, saving 5M INR, and integrating trade approvals, settlements, and securities management (Node.js, React, PostgreSQL).
• Refactored the Interest Accrual service, cutting API response time from 2 minutes to 6 seconds using Upsert, bulk data fetching, and in-memory updates (Javascript,Sequelize ORM).
• Reduced database load by shifting from Winston to RabbitMQ for asynchronous logging, improving efficiency by 40%. This decoupling of logging from core operations enhanced parallel processing, optimizing system performance and scalability.
• Desgined REST API’s with CRUD support with stored procedures and CTE for handling complex data
• validations in the database, reducing the need for application-layer checks resulting in a 50%
• improvement in data retrieval efficiency,minimize network calls.
• Implemented distributed transactions across multiple services, ensuring atomicity through centralized rollback and commit mechanisms. This ensured data consistency and integrity, crucial for reliability in a microservices-based architecture.

Jun 2023 – May 2025 · 1 yr 11 mos

• Led the development of the TITAN Project, replacing the third-party Fundware system, resulting in savings of over 5 million INR for Fund Managers. Developed the Interest Accrual service, reducing API response time from 2 minutes to 6 seconds. Designed and deployed a pod for the titan-api microservice, integrated with a Jenkins pipeline for automated CI/CD. Configured kube-dev.yml for deployment with 2 replicas, a rolling update strategy, and resource limits of 2 CPU cores and 2GB memory, optimizing performance on AWS Graviton. Desgined REST API’s with CRUD support with stored procedures, CTE, RDBMS for handling complex data validations in the database, reducing the need for application-layer checks resulting in a 50% improvement in data retrieval efficiency,minimize network calls. Reduced database load by shifting from Winston to RabbitMQ for asynchronous logging, improving efficiency by 40%.This decoupling of logging from core operations enhanced parallel processing, optimizing system performance and scalability. Implemented distributed transactions across multiple services, ensuring atomicity through centralized rollback and commit mechanisms. This ensured data consistency and integrity, crucial for reliability in a microservices-based architecture.

Jun 2022 – May 2023 · 11 mos · Kharagpur, West Bengal, India · On-site

• Guided 100+ students in Data Structures and Algorithms, enhancing technical proficiency.
• Provided detailed explanations of key concepts, aiding in problem-solving strategies.
• Facilitated hands-on implementation of data structures, boosting academic performance.

Apr 2019 – May 2019 · 1 mo · Bhopal, Madhya Pradesh, India

• Learned about the working of Auxiliary Converter based on 3*130 IGBT Converter used in Traction.