Sr. Director, Enterprise Intelligence

JM Huber Corporation•Atlanta, GA

About The Position

The Senior Director, Enterprise Intelligence defines, builds, and leads J.M. Huber's enterprise capability 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, enable trusted data and actionable insights, support enterprise performance management, promote responsible AI adoption, and scale automation. Reporting to senior IT leadership, the Senior Director connects business priorities with technology capabilities. The position partners with executive leadership, business functions, and Information Technology teams to develop enterprise intelligence strategies, decision-support capabilities, governance frameworks, and measurable business outcomes. The role builds the capability from the ground up, including organizational design, talent development, enterprise architecture, governance, adoption programs, and delivery models that support long-term growth and digital transformation.

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.
Establish 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 intelligence capabilities that improve decisions, operational performance, and business outcomes.
Lead enterprise communication, stakeholder engagement, and change initiatives to drive adoption and business value.
Establish the target-state enterprise data architecture and information management strategy.
Lead development of data governance, stewardship, quality, security, and ownership frameworks.
Guide the transition from fragmented reporting environments to a scalable enterprise data platform with common definitions and trusted information assets.
Ensure data assets are governed, accessible, aligned with business requirements, and suitable for future AI and advanced analytics.
Set enterprise strategy for reporting, analytics, performance measurement, and executive decision support.
Lead development of KPI frameworks, executive dashboards, financial and operational reporting, and management scorecards.
Build a federated analytics model with business-embedded analysts, Power BI super users, subject matter experts, and Enterprise Intelligence resources.
Implement self-service reporting and analytics while maintaining governance and consistency.
Ensure reporting and analytics investments deliver measurable value and support strategic decision-making.
Define and execute the enterprise AI strategy, roadmap, and governance framework.
Identify, prioritize, and scale AI and automation opportunities that improve productivity, efficiency, and business performance.
Develop AI policies, guardrails, governance, risk management, and responsible AI standards with relevant stakeholders.
Lead AI adoption through education, enablement, and change management.
Sponsor and expand the AI Champion Program to build AI literacy, encourage innovation, and accelerate responsible AI use.
Build and lead an Enterprise Intelligence organization spanning data architecture, business intelligence, analytics, AI, and automation.
Develop talent, succession plans, career paths, and leadership capabilities.
Establish portfolio governance and prioritization processes aligned with enterprise priorities.
Lead strategic vendor and delivery partner relationships.
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 and govern 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 initiatives.
Partner across IT to resolve complex issues, govern technical decisions, and mitigate delivery risk.