•Designed and developed backend services using Java and Spring Boot to support warehouse automation workflows (e.g., order processing, task orchestration) across distributed systems.
•Built and maintained RESTful APIs for inventory updates, task assignments, and event handling, ensuring smooth communication between warehouse systems and automation tools.
•Implemented event-driven architecture using Apache Kafka, enabling real-time data flow and reducing 30% processing latency.
•Developed Python-based analytics and automation scripts to process warehouse operational data and support basic AIdriven insights, improving decision-making and reducing manual analysis efforts.
•Developed a Docker-based workstation emulation system to simulate warehouse scenarios, improving testing efficiency and reducing dependency on physical environments.
•Designed and optimized database solutions using PostgreSQL and MongoDB to manage high-volume operational data efficiently.
•Integrated Redis caching to improve the performance of frequently accessed data, achieving sub-100ms (under 0.1 seconds) API response times during peak operations.
•Used Azure Data Explorer and logging tools to analyze distributed system events and troubleshoot issues across services.
•Deployed microservices on Azure using Docker & Kubernetes, ensuring scalable and reliable warehouse automation operations.
•Created technical documentation and system workflows, reducing recurring production issues by 20–25% and improving team efficiency.