◦ Implemented a REST API for location-based scheduling of bulk device operations in XMS using Node.js, MongoDB, and Kafka. This system utilizes a cron job for timely execution and a message queue to manage large device ID responses.◦ Increased system throughput by 40% through parallel processing and batch-handling techniques, enhancing the efficiency of device updates and operations.◦ Developed and scaled a system to process and claim large datasets of device IDs, using batch processing to improve throughput and reduce latency by over 50%, leveraging MongoDB aggregation and parallel processing.◦ Improved API performance by 30% using asynchronous data calls on MongoDB.◦ Mitigated rate-limiting issues by extracting data from PostgreSQL and Kafka, reducing usage of Redis by 20%, and enhancing monitoring with Elastic logs.◦ Developed backend functionality to display audit logs for scheduled restart and upgrades to the clients.◦ Collaborated to implement a feature ensuring 100% accurate placement of students during session creation through API calls using Meteor.js, and MongoDB.◦ Implemented an access control feature to verify user eligibility for report downloads.◦ Engineered a React.js component using MobX state management to dynamically display off-wall participant counts.◦ Migrated 3 components from Angular.js to React.js improving UI/UX.◦ Migrated 23 repositories from Bitbucket to GitHub and established Jenkins multi-branch pipelines with configured webhooks for GitHub repository commits.◦ Developed 10 visualizations on AppSmith by writing SQL queries and javascript functions.◦ Led the upgrade of Node.js from version 14 to version 18 across 10 repositories, enhancing performance and security.

◦ Strengthened resiliency in issuing cards to hotel partners with a success rate of 97%.◦ Deployed an AWS Standard Queue.◦ Integrated the queue with 2 microservices.◦ Engineered a scheduler with the provision of scalability up to processing 1000 requests each time.