We are looking for a Head of Data Governance who will lead Eurowag's data governance function and own how the company defines, owns, and trusts its data. This is a leadership role covering four connected disciplines: governance and the KPI framework, data quality and observability, metadata, catalog, lineage and data contracts, and master data and golden records.
This role combines deep data governance expertise with the ability to influence senior stakeholders across the business. You will set the multi-year vision for how Eurowag defines, owns, and trusts its data, and then deliver it, so that a number means the same thing in a board pack, a management report, a predictive model, and an investor disclosure. You will also own the commercial and delivery relationship with our external data governance partner.

• Substantial experience leading a data governance, data management, or data quality function at scale, including leading teams through other managers
• Proven track record establishing governance in an environment where numbers are externally reported, such as a listed company or a regulated industry, and understanding of what a definition change means when it moves a disclosed metric
• Demonstrated experience implementing federated or hub-and-spoke governance in practice, not only designing the target operating model
• Strong working knowledge of a modern Microsoft data stack (Microsoft Fabric, OneLake, Purview) alongside data contracts, logical data modeling, and master data management
• Experience owning a significant vendor or partner relationship, including commercial terms, scope milestones, and delivery quality
• Excellent stakeholder management and communication skills, with the ability to hold a room of commercial and finance leaders and explain why a definition matters in their language
• Experience in multi-country, multi-entity environments, ideally including post-acquisition data integration
• Experience in mobility, logistics, transport, fintech, or enterprise software is preferred
• Working knowledge of the EU regulatory landscape as it applies to data (GDPR, ISO 27001), sufficient to partner effectively with Compliance
• Proficiency in governance and delivery tooling such as Purview or equivalent catalog platforms, JIRA, Confluence, and Miro

• Define and own the multi-year data governance strategy and roadmap, aligned to the Data & AI mission themes and resilient to the SAP migration, the Microsoft Fabric platform transition, and future acquisitions.
• Lead a multi-team function through managers across governance, data quality, and metadata and master data. Hire, level, and develop those leaders and build succession within the function.
• Own the Data Governance Council operating model, cadence, RACI, and decision rights, with the DGC chair reporting into you, so that governance decisions are made rather than debated.
• Own the KPI framework, including L1 to L4 leveling, the KPI Owner and KPI Analyst model, and the standard for why a KPI exists and what business behavior it drives.
• Establish and run a controlled change window for shareholder-reported metrics, with Investor Relations alignment built into the process rather than retrofitted.
• Own data quality and observability across critical data products, including monitoring, SLOs and SLAs, schema drift detection, and issue triage, to the standard that we are the first to know our data is wrong, not our customers.
• Own metadata, catalog, lineage, ontology, and data contracts as the formal interface between data producers and consumers, and select the tooling that supports them.
• Own master data and golden records, including the Customer golden record and the logical data model across Customer, Vehicle, Transaction, Contract, Product, and Location.
• Sequence and deliver the move to governed domain ownership, starting with Credit Risk as the first test case and Fuel and Fleet Management as pilot domains, while platform and delivery remain central.
• Define FMS and partner data ownership formally within the governance process, and make partner data retrieval a governed workflow rather than a recurring escalation.
• Own the commercial model, scope milestones, and delivery quality of the external data governance partner, and lead the evaluation of the metadata framework replacement.
• Collaborate cross-functionally with Commercial, Finance and Controlling, Credit Risk, Customer Care, HR, Architecture, Compliance, IT, and Investor Relations to embed governance where data is produced and consumed.
• Represent data governance in audit and Board-facing reviews, including technology readiness reviews, with evidence and controls rather than narrative.
• Define and publish data freshness expectations covering refresh rates, processing lag, and reporting lag, and report on the function's own performance against them.
• Drive automation and AI into the governance function itself, including automated quality monitoring, metadata capture, lineage, and documentation, so that the function scales without scaling headcount.