Amazon's Fleet Procurement and Capacity Planning (FPAC) team manages a large-scale international commercial vehicle fleet across 10 European markets. This fleet depends on accurate, timely data flowing between two Fleet Management Companies (FMCs), Amazon's internal planning systems, and multiple cross-functional stakeholders.
This role owns the operational delivery and quality of all fleet data provided by FMCs (Ayvens and Arval) to Amazon. You will be the single-threaded owner ensuring that vehicle lifecycle data (from order placement through deployment, maintenance, defleeting, and remarketing) is delivered per contractual SLAs, meets validation standards, and flows reliably into the planning tools and reporting mechanisms that drive fleet capacity decisions.
This is a hands-on data operations and vendor management role. You will spend the majority of your time ensuring data reliability, resolving reporting failures with FMC technical contacts, and supporting the internal teams who depend on this data to make procurement and capacity decisions worth hundreds of millions in OPEX annually.
Please note that this is a 12 months fixed-term contract.
Key job responsibilities
1- Maintain Fleet Data Reliability
- Own the end-to-end data delivery relationship with Ayvens and Arval technical points of contact, ensuring reporting against established SLAs and contractual obligations
- Monitor, triage, and resolve data quality issues across SDR (Supply Delivery Reporting) and SRR (Supply Return Reporting) pipelines, including idle stock positions at VIN level
- Support Weekly Business Reviews and Variable Last Mile Rentals reporting cadences by ensuring upstream data is accurate and delivered on time
- Escalate systemic data failures through the appropriate FMC governance channels (Monthly Business Reviews, performance reviews).
2- Enable Planning Tools and Downstream Consumers
- Ensure data feeds into FORCE (Fleet Optimization, Requirement and Control Engine) and FAB (Fleet Allocation and Balancing) meet signal integration requirements
- Partner with the MAPS team (Mid-Term Planning) and Fleet Planning to resolve data gaps that block planning accuracy and automation
- Triage new data requests from internal stakeholders against existing data specifications; eliminate redundancy before placing additional requirements on FMCs
3- Drive Continuous Improvement
- Identify and implement process improvements to reduce manual data reconciliation effort
- Develop monitoring mechanisms to proactively flag reporting inaccuracies before they propagate into planning decisions
- Document and maintain the fleet data catalogue, including ownership, refresh cadences, quality thresholds, and known limitations
- Ensure any new fleet programs (LMR expansion, new country launches, Middle Mile integration) include data requirements in vendor agreements from the outset
4- Cross-Functional Coordination
- Align with Fleet Partnerships (FMC contractual owners), Fleet Deployment & Redeployment, Planning, and GFPA (Global Fleet Planning Analytics) on data priorities and dependencies
- Influence FMC behavior through performance metrics and contractual accountability rather than direct authority
- Represent data requirements in FMC governance forums (MBR/QBR)
A day in the life
- Bachelor's degree or equivalent
- Experience working with data analytics and using these metrics to identify problems, or experience in an operational role
- Experience in vendor management, or experience in operations and on-call support for data center facilities, mission critical plants, or production facilities
- Experience performing data analysis and troubleshooting data integrity issues
- Experience in transportation or supply chain within a high-volume logistics, manufacturing or engineering environment
- Experience working within a global company, with multi-country responsibilities
- Experience in procurement, supply chain, inventory management, contract management, lease administration or operations
- Experience managing data pipelines
- Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
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