Fleet Data Manager (Fixed-term contract), Amazon's Fleet Procurement and Capacity Planning
Amazon
London, England, United Kingdom
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
Basic Qualifications: - 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
Preferred Qualifications: - 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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