Director, Data & Analytics Enablement (Remote)

About the role

The Director, Data and Analytics Enablement will define and execute the enterprise data strategy, operating model, governance framework, and roadmap to deliver measurable business value across the organization.

Responsibilities

• Enterprise Data Strategy & Leadership
  • Own and evolve the enterprise data and analytics strategy, priorities, and multi-quarter roadmap aligned to business outcomes and measurable value realization.
  • Establish and lead the centralized data and analytics operating model, including intake, prioritization, delivery planning, funding coordination, and executive governance routines.
  • Define organizational standards, operating cadences, and success metrics for enterprise analytics delivery.
  • Serve as a trusted advisor to executive leadership on data, analytics, reporting modernization, and AI-enabled business capabilities.
• Data Platform & Architecture
  • Lead cross-functional execution across data engineering, data platform, analytics, and reporting teams to ensure scalable and reliable delivery.
  • Drive enterprise adoption of a cloud lakehouse architecture leveraging Microsoft Azure technologies, including Azure Fabric and modern analytics platforms.
  • Define and enforce reusable data patterns, semantic models, metadata standards, scalable data products, and documentation practices.
  • Partner with infrastructure and security teams to ensure governance, scalability, resiliency, and compliance across enterprise data services.
• Reporting & Analytics Modernization
  • Stabilize and modernize enterprise reporting by driving consistent metrics, trusted semantic definitions, and standardized reporting practices across Power BI, Excel, and other enterprise reporting tools.
  • Reduce duplicate reporting, inconsistent KPIs, and manual reporting processes by establishing centralized governance and delivery standards.
  • Define and track analytics performance metrics including: Adoption and utilization, Delivery cycle time, Data quality and reliability, Self-service enablement, Business value realization.
• Operational Leadership & Governance
  • Establish and manage enterprise delivery governance, steering committees, prioritization frameworks, and escalation paths.
  • Build team capacity and capability through coaching, role clarity, partner/vendor management, and operational maturity improvements.
  • Develop scalable intake and prioritization models balancing strategic initiatives, operational support, and business demand.
  • Collaborate closely with business stakeholders to align technical execution with enterprise priorities and measurable outcomes.
• AI & Emerging Technologies
  • Partner with security, architecture, and business teams to define the enterprise roadmap for AI-enabled productivity tools and workflow-integrated copilots.
  • Support governed and practical adoption of AI capabilities focused on operational efficiency and business enablement.
  • Evaluate emerging technologies and analytics capabilities that improve enterprise reporting, automation, and decision support.

Qualifications & Interests

• Bachelor’s Degree from an accredited university.
• A minimum of 10 years of progressive leadership experience in enterprise data, analytics, business intelligence, or related technology domains.
• A minimum of 5 years of proven leadership experience managing teams and building organizational structures that scale.
• Proven success building or transforming enterprise-scale data and analytics functions.
• Strategic thinker with strong operational execution discipline.
• Collaborative and highly influential across technical and business teams.
• Strong organizational leadership and change management capabilities.
• Data-driven decision maker.
• Comfortable operating in fast-paced, evolving enterprise environments.
• Strong balance of innovation, governance, and practical execution.

Preferred Qualifications

• Experience integrating common enterprise platforms such as ERP, CRM, ITSM, services workflow, or operational systems into enterprise analytics environments.
• Exposure to AI governance, enterprise copilots, and responsible AI adoption frameworks.
• Experience working in technology reseller, consulting, or professional services organizations.
• Familiarity with modern data governance, metadata management, and data product operating models.
• Experience managing strategic partners, vendors, and outsourced delivery teams.