Developed an automated data analysis solution to process complex logistics and supply chain datasets to identify operational inefficiencies. By writing custom Python scripts to parse, clean, and analyze historical transfer data, I built an automated reporting workflow that surfaces key optimization opportunities for stakeholders. The final output provides clear, actionable insights into asset redistribution. Engineered robust, automated ETL pipelines and custom tracking workflows to manage and optimize decentralized assets across a large network of facilities. This project involved consolidating diverse, messy data streams from multiple warehouse locations into a single, cohesive source of truth. Built dynamic Power BI dashboards on top of this clean data to give executive leadership complete visibility into inventory health and demand forecasting. Architected and deployed a highly scalable backend solution designed to power internal business utilities and automation tools. This project utilized a modern, robust 6-microservice architecture to ensure high availability, efficient data processing, and seamless tool integration. Managed the entire deployment process across a hybrid cloud infrastructure to ensure stable performance and security.