SG Warehouse Business Intelligence Analyst

About the team

The SG Warehouse Business Intelligence (WH BI) team is a highly technical and operations-focused unit that supports end-to-end warehouse and fulfillment performance. We work closely with Operations, Planning, Regional, and Product teams to deliver accurate, scalable, and automated data solutions that drive efficiency across inbound, outbound, inventory, and fulfillment processes.

Our team specialises in transforming complex warehouse data into actionable insights, enabling faster issue resolution, performance optimisation, and cost control. By leveraging SQL, Python, and automation tools, we build a reliable data infrastructure that supports daily operations and long-term capacity planning.

What you'll do

• Partner with Warehouse Operations, Planning, and Regional teams to provide actionable insights on key Warehouse metrics, not limited to productivity, performance and inventory health. 
• Monitor and deep dive into operational Key Performance Indicators to identify performance gaps and root causes.
• Translate operational business requirements into structured technical solutions and scalable data workflows.
• Automate manual operational reporting processes using SQL, Python, VBA, or other tools.
• Develop and maintain dashboards and monitoring systems to ensure data accuracy and timeliness.
• Optimise end-to-end reporting flow from data source (WMS / order system) to front-end dashboards.
• Support warehouse-related initiatives such as process optimisation, capacity planning, liquidation analysis, and cost efficiency projects.
• Perform ad-hoc deep dives to support urgent operational issues and drive data-backed decision-making.

Requirements

• Bachelor’s degree or above in Data Analytics, Statistics, Mathematics, Computer Science, Supply Chain, or other quantitative disciplines.
• Strong hands-on experience in SQL and Python; proficiency in Excel / Google Sheets is required.
• Experience supporting operations, warehouse, supply chain, or e-commerce fulfillment is highly preferred.
• Strong analytical thinking with the ability to break down complex operational problems.
• Detail-oriented with high standards for data accuracy and reporting quality.