TEJA REDDY

I am a software developer with 10.5 years of experience focusing on Mainframe technology and Java spring boot API. I have expertise in the complete SDLC process and possess strong programming skills in various languages. Certified in the retail domain, I thrive in fast-paced environments and have successfully contributed to multiple significant projects at Tesco. I'm committed to personal and professional growth, continuously learning new technologies to adapt to changing industry needs.

• Value Award, Received Value Award for being able to learn the Java quickly and designing the project with minimal guidance and deliver the program on time.
• Star Award: Recognized by management for taking full responsibility for the re-processing of the Loader Message project, successfully delivering it with zero defects in production

Project 1: Distribution Colleague Transformation

Project Description:

This project aimed to modernize and streamline the process of managing colleague details and schedules. Previously, colleague details were received from Zellis and schedules from WFC using a legacy black-box communication system. The transformation involved migrating to a more transparent and efficient solution by integrating data from Zellis and WSA into Denver via Java services. Colleague swipe data is now published to Kafka, enabling the Zellis payroll system to read events directly from Kafka for processing.

Responsibilities:

• Developed RESTful APIs using Java Spring Boot to receive messages from the host systems and validated them locally through Postman.
• Deployed the APIs to the Tesco Private Cloud (TPC) server, ensuring scalability and reliability.
• Designed and implemented enhancements in Denver to handle incoming messages, including writing modular and reusable code for web service calls.
• Built services in Denver to process messages from Java APIs and update the corresponding VSAM (Virtual Storage Access Method) files with colleague details efficiently.
• Contributed to overall system integration by ensuring seamless communication between Kafka, Java APIs, and Zellis payroll systems.

Project 2: Processing of Loader Messages

Project Description:

This project focused on ensuring the accurate transmission and processing of messages from the Loader system to Denver. Loader messages are generated when store orders are loaded onto trucks, but during the End-of-Day (EOD) process, these messages were often missed, causing downstream systems to lack crucial details about trucks sent to stores. Additionally, any Loader activities performed during EOD resulted in message loss and data discrepancies. The objective of the project was to implement a robust solution to handle the re-processing of missed or failed messages after the EOD process, ensuring data integrity across systems.

Responsibilities:

• Took full ownership of the project, gathering detailed requirements and specifications from the product manager.
• Designed a comprehensive solution to handle the re-processing of all Loader messages, including Picking messages, ensuring reliable message handling across scenarios.
• Implemented code changes to enable the retry mechanism for failed messages and seamless integration with existing systems.
• Created detailed test cases in Jira, documenting each step to validate the new functionality and ensure system reliability.
• Actively participated in integration testing with the Loader system, ensuring smooth communication and accurate processing post-EOD.

Project 3 : FLT Optimization

This project focused on optimizing work allocation for FLT (Forklift Truck) drivers to improve efficiency and reduce costs. Tasks such as Putaway, Replen, and Selpal were analyzed and optimized. The optimization algorithm, developed using Data Science techniques, leveraged data from Denver Depot about colleagues and tasks. This data was sent to the optimizer via web services and stored in Couchbase. The optimizer then assigned tasks to drivers, minimizing unladen travel and saving £4,000,000 annually.

Responsibilities:

• Implemented enhancements for Replen and Selpal task types, including updates to resource and task location information.
• Developed functionality to push task and resource messages to Couchbase through web service integration.
• Authored detailed end-to-end (E2E) test cases in Jira, outlining step-by-step validation for accuracy and consistency, and participated in rigorous testing efforts.
• Contributed to test automation by generating test messages received in Denver from the third-party system for Middlesbrough Depot, ensuring system compatibility.
• Delivered a demo presentation to the business team, showcasing the optimization process and its significant cost-saving benefits.

Project 4: IR05 Simplification

IR05, a critical component of store order processing in Denver, was highly complex due to multiple intertwined logics within a single codebase. This complexity led to challenges in analysis, modifications, and maintenance, making it costly and time-consuming. The project aimed to simplify IR05 by refactoring it into multiple Single Responsibility modules, reducing IO operations, improving maintainability, and lowering costs. Additionally, the project focused on creating Replen work types when stock at a selected location fell below a threshold and Selpal tasks when store units matched pallet sizes.

Responsibilities:

• Took ownership of the most complex segment, analyzing and designing a solution to handle Replen and Selpal work types across four distinct versions of the logic.
• Conducted a detailed review of existing logic, identifying and removing unused or redundant code, contributing to codebase cleanup and optimization.
• Developed a reusable copycode module to identify reserve locations from an 8,000-location chain, enabling consistent and efficient processing for both Replen and Selpal tasks.
• Designed and implemented modular solutions that adhere to the Single Responsibility Principle, ensuring scalability and ease of future enhancements.

Project 5: AMR (Autonomous Mobile Robots) – Fresh DCs Automation

This project introduced automation in Fresh Distribution Centers (DCs) using an Autonomous Mobile Robots (AMR) solution in collaboration with a third-party vendor, Geek+. The initiative aimed to enhance operational efficiency by increasing the pick rate and improving the accuracy of cage filling compared to manual processes. The proof of concept demonstrated the potential for automating key workflows, laying the foundation for broader adoption of AMR technology.

Responsibilities:

• Designed the solution for receiving and processing all inbound messages from Geek+, ensuring seamless communication with the AMR system.
• Developed code to handle and validate pick confirmation messages from Geek+, sending appropriate responses. The foundational code was leveraged to build all inbound message processing workflows.
• Implemented logic to process pick confirmation messages, creating reusable copycode for handling physical stock adjustments, including exceptions for overages and shortages.
• Proposed and designed a scalable solution for processing pallet induct messages from Geek+, utilizing reusable copycode to update file systems. This approach streamlined existing code and ensured reusability across workflows.
• Designed and built functionality to process pallet receipt messages sent to Geek+, detailing the product contents of each pallet.
• Created a solution to accept automation-ready product pallets from suppliers with reduced checks, eliminating the need for breakdowns or topping of pallets, thereby optimizing the workflow.

Date of birth:            29/09/1992
Gender:                     Female
Nationality:               Indian
Current Location:     Bangalore