Vice President, Data & Analytics

Reporting to the Chief Enterprise Business Services Officer, this executive role leads a small, global team while remaining deeply engaged in hands-on technical work across data strategy, governance, engineering, and AI initiatives.

About the role

As a player-coach, you will set the vision and direction for data and AI as strategic assets, enabling informed decision-making, operational excellence, and business growth. You will build, mentor, and retain a high-performing team while personally contributing to platform development and governance.

Responsibilities

• Leadership & strategy
  • Partner with business and enterprise stakeholders to align data initiatives with organizational priorities
  • Establish enterprise data governance and stewardship, including data ownership, quality standards, and access policies in collaboration with security, legal, and compliance
  • Manage vendor/platform costs through compute governance, storage lifecycle policies, and balancing cost/value
  • Build and retain a high-performing global team; define the operating model, hiring plan, and delivery priorities
  • Maintain strong documentation and knowledge-management practices, treating data contracts, table docs, and query patterns as first-class deliverables
• Hands-on lakehouse engineering
  • Demonstrate expert-level Databricks (or similar) skills: Delta Lake internals (MERGE/CDC patterns, OPTIMIZE, vacuum/retention, time travel), SQL warehouses, and workflow/job orchestration
  • Design and implement medallion (bronze/silver/gold) architectures with efficient load design, dedup strategy at ingestion, and grain/key discipline
  • Apply strong Unity Catalog governance: access model design, lineage, and system-table observability
• Data architecture & modeling
  • Apply proven dimensional-modeling expertise (Kimball-style facts/dims): define and enforce fact grain, conformed dimensions, and surrogate-key discipline
  • Integrate multi-ERP systems (SAP, Dynamics, Navision, JDE/E1, IFS or similar)
  • Design CDC/replication architectures that minimize storage and compute requirements
• Assessment & redesign capability
  • Lead platform assessments and rationalization: data-quality profiling, source-to-target lineage reconstruction, and storage/compute cost reduction
  • Develop and implement a continuous data-quality framework with automated grain/duplication/reconciliation tests in pipelines (e.g., dbt tests, Delta Live Tables expectations)
  • Apply financial reconciliation mindset: tie warehouse facts to reported financials (orders vs bookings vs GL) and document legitimate divergences
  • Plan pragmatic migrations while maintaining certified models and executive dashboards
• AI & advanced analytics
  • Define and drive AI/ML and generative-AI strategy: identify, prioritize, and sequence high-value use cases tied to measurable business outcomes
  • Establish responsible-AI and model governance: evaluation, monitoring, data-privacy, and risk controls for predictive and generative systems
  • Enable self-service analytics and citizen development through governed data products and a trusted semantic layer

Qualifications

• Bachelor’s degree in Data Science, Information Systems, Computer Science, or related field — or equivalent experience
• 10+ years of progressive experience in analytics, business intelligence, and data administration
• Expertise in data governance, data architecture, BI platforms, and cloud data technologies
• Strong proficiency in data modeling and analytics methodologies
• Demonstrated people-leadership: building, mentoring, and retaining technical teams while remaining hands-on in the platform
• Experience setting AI/ML and analytics strategy and standing up data or AI governance at enterprise scale
• Strong executive communication and strategic planning skills