Jun 2024 – Jun 2025 · 1 yr

Jun 2024 – Jun 2025 · 1 yr

• Developed a Gmail API-based service to build a chat-panel ticketing system, migrating from Amazon SES to Gmail API, resulting in improved stability and cost savings of approximately 4 lakhs. Developed and optimized a high-performance WhatsApp messaging campaign service using Meta APIs, capable of sending billions of messages at scale. Leveraged multiple message templates (e.g., carousel, image, video) for diverse campaign requirements. Achieved 13k requests per second (RPS) throughput on a standard EC2 instance, utilizing Golang, Kafka, and Redis for asynchronous message queuing, real-time processing, and efficient data caching. Designed and implemented an analytics dashboard within two weeks using ClickHouse DB, achieving a dramatic reduction in API data load times from several seconds to milliseconds by leveraging materialized views and table engines in ClickHouse with Node.js. Built and scaled a multi-tenant message service microservice processing 15M+ messages/day across clients, merchants, and channels (Meta/WhatsApp); supported both sync/async flows with p95 < 250ms; powered real-time chat panel for 5K+ concurrent sessions; and improved reliability with retries, idempotency.

Jun 2022 – Jun 2024 · 2 yrs

• Designed and constructed asynchronous API cron jobs to retrieve aggregated performance data from Elasticsearch. This data was
• previously sourced from SQL databases, resulting in a substantial reduction in cron job duration from 6-7 hours to 3-4 hours..
• Java, ElasticSerach
• Developed payout system and rule engine for merchant payout, this system ensures that all the orders placed with a particular
• merchant receives his daily payout after all commission applied after T+1 day.Nodejs, SQL, rabbitMq, kafka, redis
• Played a key role in formulating and designing a rule engine for the team, addressing intricate use cases and encompassing all
• scenarios involving merchants and agents. Java, MongoDB
• Engineered APIs to compute aggregated data for a substantial number of merchants and agents, significantly reducing API
• response time from an average of 1000ms to 300-400ms. Leveraged MongoDB’s aggregation pipeline to implement this innovative
• solution. Spearheaded the creation and upkeep of multiple APIs, resulting in notable improvements in average response times.
• Java, MongoDB
• Developed an incentive rule engine project at my current organization, Using Java Spring Boot for API building. Responsible for
• creating interconnected services, implementing message buses(Kafka) and real-time processing, as well as working with
• non-relational databases(MongoDB).
• Worked on ONDC project payout system for the organisation ,build payout system for it. Also worked on bus ticket payout system
• back end with efficient latency, here build a feature where customer amount is gratified in T+1 days. Technology used were
• NodeJs, RabbitMq, SQL.
• Knowledge of automated build / continuous delivery, experience of Jenkins, deployment.
• Maintained and worked on report generation system for financial and business purpose.
• Setup and fixed whole new legacy system from scratch and migrated to other entity of organisation knowing whole microservice

Jan 2022 – Jun 2022 · 5 mos

Nov 2020 – Jan 2021 · 2 mos