Procurement & Supply Chain

Procurement & Supply Chain System - Scottish Water

Role: Software Development Engineer (SDE II)
Technologies Used: Java, Spring Boot, PostgreSQL, Python, Spark, Jenkins, Docker, Kubernetes, Angular, AWS, SQL Server, Spark

Project Overview:
As part of the team at Scottish Water, I developed and optimized a Procurement and Supply Chain System to enhance the efficiency of procurement processes, data management, and decision-making. The system streamlined procurement activities, integrated large datasets, and provided actionable insights to stakeholders, contributing to cost reduction and improved operational performance.

Key Features:
• Backend Services Development: Engineered scalable backend services using Java and Spring Boot, ensuring efficient handling of large volumes of procurement data and integration with external systems.
• Data Optimization: Developed complex SQL queries and optimized stored procedures to improve the performance of data retrieval and manipulation, resulting in a 17% performance improvement during migration from Oracle to SQL Server.
• Data Automation: Designed and implemented Python-based scripts to automate ETL workflows (Extract, Transform, Load), ensuring seamless data processing and transformation for reporting and analytics.
• Distributed Data Processing: Utilized Apache Spark for distributed processing of large datasets, enhancing system performance and scalability, particularly in handling procurement data and generating insights.
• Procurement Dashboards: Built dynamic, user-friendly front-end dashboards with Angular and Material UI to provide real-time monitoring of procurement activities, improving user engagement by 25%.
• CI/CD Pipelines: Optimized CI/CD pipelines using Jenkins, Docker, and Kubernetes, reducing deployment cycle time by 30% and ensuring the reliable delivery of updates to the system.
• Collaboration with Stakeholders: Worked closely with business teams to align technical solutions with procurement strategies, ensuring the system provided actionable insights and aligned with the business’s cost-saving goals.

Impact:
• Improved Data Processing Speed: The system’s data optimization and migration from Oracle to SQL Server resulted in a 17% improvement in performance, significantly reducing query execution times and improving operational efficiency.
• Enhanced Forecasting Accuracy: The CPI-based price prediction models improved forecasting accuracy by 18%, enabling procurement teams to better anticipate price fluctuations and optimize budgets.
• Data-Driven Decision Making: The development of dynamic procurement dashboards empowered stakeholders to access real-time insights, which improved decision-making and engagement metrics by 25%.
• Cost Reduction: By automating financial document generation and procurement workflows, the system reduced manual errors and improved the overall efficiency of procurement operations, resulting in cost savings.
• Increased System Scalability: The use of Apache Spark for distributed data processing enabled the system to handle large datasets efficiently, supporting future growth without compromising performance or speed.
• Optimized CI/CD Pipeline: Streamlined CI/CD processes using Jenkins, Docker, and Kubernetes, reducing deployment cycle times by 30%, enabling faster and more reliable updates to the system.
• Seamless Integration: Successfully integrated data across different systems, reducing data silos and ensuring seamless communication between internal procurement tools and external suppliers, improving overall workflow integration.
• Risk Mitigation: The automated ETL workflows and real-time analytics provided actionable insights into procurement activities, helping the team identify and mitigate potential risks early in the process, ensuring smoother operations.
• Compliance and Reporting: The solution helped align procurement processes with regulatory requirements, improving compliance and ensuring that reports met both internal and external auditing standards.