Piyush Yadav

Created Adaptor Tool as a Microservice whose task is to automate the file upload process. The upload time has been reduced by 80 percent and file processing time has been reduced by 300 percent on average. Orchestrated the migration of services to AWS ECS, optimizing deployment with zero downtime and automated production deployments. Headed the Centralized Distribution Management System (CDMS), introducing features like Brands Sales Order Integration, warehouse management and enhancing code and query performance. Designed a data pipeline queue using the Kafka Pub/Sub model, resulting in a 200 percent increase in data processing speed. Successfully implemented Goods Receipt Note (GRN) functionality and integrated with Stock-One for managing inventory on daily basis. Leveraged various AWS services including S3, EC2, ECR, Lambda, SQS, ALB, TG, and Task Definitions for a scalable infrastructure.

Collaborated with Salesforce to create Collection CRM microservice that increases productivity, reduces costs, and ensures the scalability of the collection team by 90 percent. Created a Fraud Management System to identify users who repeatedly attempt to access our system with fake documents and block them from future use and containerized the whole service which helps in reducing AWS cost by 30 percent. Increased 40 percent of productivity of team by deploying functionalities on the dashboard and automating manual tasks and build various dashboards for Product, MIS and Collection Team.

Created a website in Django for blogs and functionality includes Authentication and Authorization, update and delete the blog, Image add functionality, mail support. Tech Stacks: Docker, Kafka, ECS, ECR, S3, AWS Lambda, SAM, Redis, Node.js, HTML, CSS, Bootstrap. Developed a power-saving methodology Tool by training a predictive model on various parameters, including humidity, day, month, and time, to optimize lighting costs. The model accurately predicts when the lighting component should be activated, resulting in efficient energy consumption and cost reduction. Tech Stacks: Python, Jupiter-lab, Matplotlib, Seaborn, Altair, Multiple Linear Regression.