- On the Amazon Aurora Heat Management team, where the primary goal is finding the database’s highest usage rate and sharding the clusters accordingly for performance improvements- Created a Heat Management Simulator in Java using Amazon’s internal framework Coral to perform in-memory services on MySQL/PostgreSQL database clusters, validate the functionality of services, and perform failure and chaos testing- Using AWS Cloudwatch to generate tasks running metrics collection workflow from shards and routers - Deployed to multiple virtual machines through Apollo, Amazon’s internal distributed deployment systems, with functionality similar to EC2 with Elastic Load Balancing- Introduced integration and end-to-end functional test flow with validation mechanisms in the CI/CD pipeline to ensure automatic deployment and prevent error propagation to other environments and stages with AWS CDK- Participated in daily scrum meetings, git for source control, resolving CRs, and other agile ceremonies

- Applied algorithmic solutions to enhance inventory processes, achieving a delicate equilibrium between supply requisites, budgetary constraints, and spatial limitations- Leveraged data analytics and software tools with SQL to make informed decisions regarding inventory management, enhancing overall efficiency and cost-effectiveness- Implemented inventory management software and RFID systems for precisely locating parts within the warehouse