Head of Data & Analytics

• Do you have the vision and leadership experience to define the future of Data & Analytics, owning the strategy, platform, governance, and operating model for a global enterprise?
• Are you motivated by building trusted data foundations that enable better decisions, power AI capabilities, and deliver lasting business impact?
• Do you enjoy influencing executive stakeholders and driving a data-driven culture that turns information into business value at scale?

Practical Information

Location: EU / EEA - any of SoftwareOne locations | Work Arrangement: Hybrid | Contract type: Full-time | Reports to: Chief Product & Technology Officer | Visa Requirements: Valid visa for country of employment | Language Requirements: Fluent/professional English, written and verbal, German is a plus

As our Head of Data & Analytics, you will lead and evolve our enterprise Data & Analytics function, transforming data into a trusted, scalable, and business-critical capability that delivers measurable value across the organization. You will own the enterprise data platform, data engineering standards, governance, and analytics enablement, while partnering with business domains to deliver trusted insights, reusable data products, and impactful outcomes. Leveraging a modern ecosystem built on Microsoft Fabric, Databricks and Power BI, you will drive simplification, stronger governance, and the scalable growth of data and analytics, capabilities across the business.

Key responsibilities

• Strategy & Operating Model: Define and execute the enterprise Data & Analytics strategy, target operating model, roadmap, and investment priorities, aligned with business and technology objectives
• Data Products & Analytics Delivery: Lead the delivery of curated data models, reusable data products, dashboards, and analytics services that support timely decision-making and measurable business outcomes
• Enterprise Data Platform: Own the shared data platform, architecture, ingestion and processing patterns, engineering standards, reliability, security, observability, capacity, and cost management
• Governance & Trust: Establish and maintain enterprise standards for data quality, ownership, access, lineage, data cataloging, lifecycle management, compliance, and operational controls
• Domain Partnership & Enablement: Apply a tiered engagement model that meets business domains at their level of capability, maturity, and risk, from full-service delivery to governed self-service
• Leadership & Transformation: Build and lead a high-performing global team across data architecture, platform engineering, data management, analytics delivery, and enablement; drive organization transformation, consolidate platforms and simplify the analytics estate