The Operational Excellence Analyst in Global 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.
The role requires deep technical proficiency in data extraction, transformation, and analysis combined with the ability to translate complex findings into actionable recommendations for senior leadership. You will design and implement end-to-end analytical solutions: from raw data ingestion through insight delivery, working across Andes/Redshift, Athena, S3, Python automation, and visualization platforms.
We are seeking a technically strong specialist with passion for data engineering, process improvement, and operational analytics someone who can independently mine complex datasets, identify systemic patterns, and drive measurable improvements to customer delivery experience across EU marketplace.
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 optimization) 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
- Drive the process improvement roadmap with data-backed proposals influencing decision-making at all levels through rigorous quantitative analysis
- Perform large-scale data mining across multiple database systems (Redshift, Athena, DynamoDB) to identify patterns in transship flows, delivery accuracy, and network performance
- Collaborate with technology teams to translate analytical findings into system requirements, new features, and configuration changes
- Develop and document automated data quality checks and monitoring frameworks for critical operational metrics
- Act as technical enabler for front-line teams building tools that surface defects, identify root causes, and track corrective action effectiveness
A day in the life
- Write and optimize complex SQL queries across multiple data sources to investigate why customer delivery promises were missed —tracing issues back to specific products, warehouses, or shipping routes
- Build and maintain Python scripts that automate daily/weekly data pulls, transformations, and reporting deliverables
- Collaborate with Business Intelligence Engineers, Program Managers, and Finance Analysts to develop scalable metrics frameworks
- Perform deep-dive investigations on specific shipments or orders, then scale findings using statistical methods to quantify network-wide impact
- Translate operational challenges raised by business teams into structured analytical problems — designing technical solutions that address the root cause, not just the symptom
- Partner with tech teams to define data requirements and validate system changes through pre/post analysis
- Present data-driven recommendations to senior leadership with clear quantification of customer and cost impact
- Develop and maintain scheduled data transformation jobs for automated reporting
- Monitor automated alerting systems and triage emerging operational issues using real-time data
About the team
The Global Operational Excellence (GOX) team drives operational improvements across Amazon’s EU fulfillment network and ROW. We work at the intersection of technology and operations to optimize how inventory is placed, moved, and delivered reducing costs while improving customer experience. Our team leverages large-scale data analysis, automation, and cross-functional collaboration to solve complex supply chain challenges across Inbound Speed, Delivery Estimate Accuracy (DEA), and network performance.
- Bachelor's degree or equivalent qualification in Math, Engineering, Science or Business
- Experience in ETL management/data pipeline
- Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages
- Experience working with operations and business teams to communicate problem impacts and understand business requirements
- Experience in creating process improvements with automation and analysis, or experience in building financial and operational reports/data sets that inform business decision-making
- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
- Experience in data analytics, business intelligence, or data engineering within operations/supply chain
- Python programming experience writing scripts for data manipulation (pandas, numpy), automation (boto3, scheduling), and basic statistical analysis
- Master's degree or above in supply chain management, operations, engineering, analytics or related field
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Knowledge of supply chain management concepts - forecasting, planning, sourcing, optimization and logistics or equivalent
- Experience with statistical methods (e.g., A/B Testing, Regression)
- Experience in logistics, transportation, supply chain, import/export operations, or data entry/data administration
- Experience in automation or monitoring frameworks, deployment or development
- Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
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The minimum gross base salary for this position is listed below. The base salary listed corresponds to working on a full-time basis. For part-time hours, the salary will be pro-rated.
Amazon reserves the right to offer a higher salary and/or level, depending on the candidate's skills, competencies, and experience. Amazon's package may include a sign on payment. In addition, the candidate may be eligible to participate in a restricted stock unit scheme operated independently by Amazon.com Inc. in USA.
Your recruiting team will share final salary and any restricted stock unit scheme if applicable, depending on skills and requirements.
In addition to statutory benefits, and those applicable to the relevant CBA, company supplementary benefits may apply subject to further terms.
Milan, ITA - 50,600.00 EUR Annually
