Sr. Director, Enterprise Intelligence

Huber•Atlanta, GA

About The Position

The Senior Director, Enterprise Intelligence defines, builds, and leads J.M. Huber’s enterprise capabilities for data, analytics, business intelligence, artificial intelligence, and automation. The role establishes the vision, strategy, governance, architecture, operating model, and organizational capabilities needed to turn enterprise data into business value. It is accountable for an integrated Enterprise Intelligence function that enables trusted data, actionable insights, enterprise performance management, responsible AI adoption, and scalable automation. Reporting to senior IT leadership, the Senior Director serves as a strategic bridge between business priorities and technology capabilities. The role partners with executives, business functions, and Information Technology teams to develop enterprise intelligence strategies, decision-support capabilities, governance frameworks, and measurable business outcomes. The position builds the capability from the ground up, including organizational design, talent development, enterprise architecture, governance, adoption programs, and delivery models supporting long-term growth and digital transformation. The role leads enterprise intelligence strategy and governance; enterprise data architecture and information management; business intelligence, analytics, and performance management; AI strategy, governance, and enablement; organizational development, delivery, and value realization; and technical strategy, architecture oversight, and advisory leadership. The company describes employee safety, health, and well-being as its highest priority and emphasizes professional and personal development, inclusion, dignity, respect, and strong performance.

Requirements

Bachelor’s degree in information systems, Computer Science, Engineering, Analytics, Data Science, Business Administration, or a related discipline.
15+ years of progressive leadership experience in data, analytics, business intelligence, information management, enterprise applications, AI, or digital transformation.
Proven success building and leading enterprise-scale data, analytics, AI, or digital transformation capabilities.
Hands-on experience designing and implementing enterprise data architectures, platforms, integrations, analytical models, business intelligence solutions, and AI capabilities.
Experience establishing enterprise governance frameworks, operating models, and organizational capabilities.
Proven ability to influence executive stakeholders, lead cross-functional transformation, and manage strategic vendors and delivery partners.
Strong understanding of enterprise data architecture, data governance, analytics, business intelligence, information management, and modern data platforms.
Knowledge of AI, Generative AI, intelligent automation, machine learning, and emerging AI technologies.
Ability to develop enterprise strategies and translate complex concepts into actionable business outcomes.
Strong organizational leadership, portfolio management, financial management, and change leadership capabilities.
Exceptional communication, relationship management, and executive influencing skills.
Demonstrated ability to build high-performing teams and develop future organizational leaders.

Nice To Haves

Master’s degree.

Responsibilities

Develop and execute the Enterprise Intelligence strategy, roadmap, and operating model, establishing priorities, investments, governance processes, and organizational capabilities aligned with enterprise objectives.
Advise business and technology leadership on data, analytics, business intelligence, AI, and automation strategies; translate business priorities into capabilities that improve decisions, operational performance, and business outcomes.
Lead enterprise communications, stakeholder engagement, and organizational change initiatives to drive adoption and business value.
Establish the target-state enterprise data architecture and information management strategy for analytics, reporting, and AI.
Develop data governance, stewardship, quality, security, and ownership frameworks; oversee the transition from fragmented reporting environments to a scalable data platform with common definitions and trusted information assets.
Ensure enterprise data assets are governed, accessible, and aligned with business requirements while supporting future AI and advanced analytics capabilities.
Establish enterprise strategies for reporting, analytics, performance measurement, and executive decision support.
Lead development of enterprise KPI frameworks, executive dashboards, financial and operational reporting, and management scorecards.
Build a federated analytics model involving Enterprise Intelligence resources and business-embedded analysts, Power BI super users, and subject matter experts.
Implement self-service reporting and analytics capabilities while maintaining governance and consistency; ensure investments deliver measurable value and support strategic decisions.
Define and execute the enterprise AI strategy, roadmap, and governance framework; identify, prioritize, and scale AI and automation opportunities.
Develop AI policies, guardrails, governance, risk management, and responsible AI standards in partnership with Cybersecurity, Compliance, Architecture, and other stakeholders.
Lead AI adoption through education, enablement, and change management; sponsor and expand the AI Champion Program.
Build and lead a high-performing Enterprise Intelligence organization covering data architecture, business intelligence, analytics, AI, and automation.
Develop talent, succession plans, career paths, and leadership capabilities; establish portfolio governance and prioritization aligned with enterprise priorities.
Lead strategic vendor and delivery-partner relationships and define and measure business outcomes, value realization, adoption metrics, and return on investment.
Set strategic direction for enterprise data, analytics, business intelligence, AI, integration, and architecture; establish technology standards, architecture principles, solution design practices, and enterprise models.
Review and approve complex architectures for scalability, interoperability, security, maintainability, and business alignment.
Guide platform modernization, technology selection, vendor evaluation, and innovation; partner across IT to resolve complex issues, govern technical decisions, and mitigate delivery risk.