Zeeshan Shaikh Email and Phone Number

Grad Teaching Assistant for ESE 554 Computational Models For Computer Engineers(Data Structures and Algorithms) - Fall 2023

• Sales Analytics Platform: Developed scalable backend microservices using Java and Spring Boot to efficiently process sales data across 20 brands, generating KPIs and reports to empower business intelligence, and optimize operational performance. The metrics and reports were visualized on a dynamic Angular dashboard.• Data Pipelines: Implemented data processing pipelines utilizing Spring Boot to ingest, and distribute POS data into transactional and brand-specific databases via Apache Kafka, boosting real-time data processing and analytics by 70%.• Responsive UI: Led migration of legacy System Health Monitoring application(frontend) to Angular 10, achieving an 85% reduction in content load time, and a better user experience for stakeholders.• Testing: Conducted code reviews and wrote unit tests using JUnit, achieving a code coverage of 83%.• Deployment: Utilized Jenkins for CI/CD to automate the build and deployment of Docker containers to Azure Kubernetes Service (AKS).

• Dealership Platform: Developed REST APIs using microservice architecture in Java and Spring Boot for vehicle inventory management tool, enabling efficient CRUD operations and advanced search capability.• Email Notification Service: Implemented scalable email automation platform using Python and Azure Logic Apps to deliver personalized emails with inventory updates, personalized reports and operational notifications.• Bug Reduction: Enhanced code quality through robust unit and integration testing, adopting Test-Driven Development (TDD) and resulting in a 40% reduction in production bugs.

1. Overhauled the user interface (UI) of an internal application utilizing HTML, CSS, and JavaScript, implementing modern design principles and responsive techniques to enhance user interaction and visual appeal.2. Acquired hands-on experience within the Engine Shop environment, leveraging database querying techniques to extract critical data related to the quality check process for crankshafts manufacturing. This involved proficiently navigating database structures and executing complex queries to retrieve and analyze vital service-triggered quality check data.