Director, Data & Analytics Enablement (Remote)

Trace3•Dallas, TX

1d•Remote

About The Position

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. This leader will partner closely with business stakeholders, IT leadership, and cross-functional teams to modernize reporting, improve data consistency and trust, and build scalable analytics capabilities leveraging Azure-based technologies and modern data platform practices. In addition, this role will also help shape the organization’s approach to AI-enabled productivity, governed analytics, and workflow-integrated copilots.

Requirements

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.
Strong leadership experience in enterprise data strategy, roadmap development, and value realization initiatives.
Demonstrated ability to influence senior leaders and drive alignment across cross-functional organizations.
Deep understanding of: Modern data platforms and lakehouse architectures, Semantic modeling concepts, Enterprise reporting and analytics governance, Data engineering and analytics delivery practices.
Experience implementing trusted semantic approaches and improving consistency of enterprise reporting metrics and definitions.
Hands-on familiarity with Azure-based analytics ecosystems, including Power BI and Microsoft Fabric.
Strong communication and executive presentation skills with the ability to translate business priorities into technical delivery outcomes.
Experience building operational governance models, prioritization processes, and enterprise delivery cadences.
Proven ability to lead through influence in matrixed enterprise environments.
Strategic thinker with strong operational execution discipline.
Collaborative and highly influential across technical and business teams.
Strong organizational leadership and change management capabilities.
Customer and business outcome oriented.
Data-driven decision maker.
Comfortable operating in fast-paced, evolving enterprise environments.
Strong balance of innovation, governance, and practical execution.

Nice To Haves

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.

Responsibilities

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.
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.
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.
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.
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.