DESCRIPTION The Operational Excellence Analyst in Integral Operational Excellence (GOX) drives data-driven performance improvements across Amazon’s EU Inbound Supply Chain operating in a cross-functional environment with Cross Dock and Fulfillment Center Operations, Transportation, Analytics, and Planning Systems teams.
This role owns the technical analysis and automation behind regional Inbound Speed and Delivery Estimate Accuracy (DEA) metrics. You will build scalable data pipelines, write production-grade SQL against petabyte-scale warehouses, and develop analytical tooling to identify, quantify, and eliminate placement defects, transportation disruptions, and supply chain backlog connecting systemic root causes to shop-floor impact and customer delivery outcomes. You will develop automated monitoring systems, statistical models, and simulation frameworks to surface improvement opportunities before they impact customers.



Your work will span from exploratory data analysis on large-scale datasets to building self-service tools that enable business partners to make data-driven decisions in real time.
Key job responsibilities
- Own the data infrastructure behind Inbound Speed and DEA metric reporting building automated ETL pipelines, scheduled queries, and alerting mechanisms
- Write advanced SQL (window functions, CTEs, recursive queries, query optimisation) against large-scale data warehouses (Andes/Redshift, Athena) to perform root cause analysis on placement and transportation defects
- Develop Python-based automation for data processing, anomaly detection, and reporting workflows reducing manual intervention and accelerating insight delivery
- Build statistical models to quantify the impact of transportation disruptions, supply chain backlog, and placement deficiencies on customer delivery promises
- Design and maintain dashboards and self-service analytical tools (QuickSight, automated reports) enabling stakeholders to detect problems ahead of customer impact
- D

📌 Operational Excellence Analyst (Madrid)
🏢 Amazon. Com
📍 Madrid