Sr. Director, Enterprise Data, Analytics, AI & Automation

Job Description

The Senior Director of Enterprise Data, Analytics, AI and automation is responsible for defining and executing the enterprise strategy for data, analytics, artificial intelligence, and intelligent automation. This leader will build the foundational capabilities, governance, platforms and operating models required to transform the data into a strategic asset, enable AI-powered business outcomes across the organization.

Reporting to the Chief Information Officer, the role will partner closely with business leaders, technology teams, and external partners to modernize decision-making, automate business processes, accelerate innovation, and deliver measurable business value through data-driven intelligence.

The successful candidate will lead the organization's Data & AI transformation agenda, ensuring that analytics, automation, machine learning, generative AI, and agentic AI capabilities are implemented responsibly, securely, and at scale.

Major Responsibilities

(20%) Enterprise Data/AI Strategy and Portfolio Management
Define and execute the enterprise Data, Analytics, AI, and Automation strategy aligned with business priorities and long-term corporate objectives.
Develop and maintain a multi-year roadmap for data modernization, AI adoption, advanced analytics, and intelligent automation.
Establish enterprise investment priorities, performance metrics, and value realization frameworks for Data & AI initiatives.
Advise executive leadership on emerging technologies, AI trends, opportunities, and risks to enable informed strategic decisions and responsible innovation.
Prioritize the enterprise Data & AI portfolio in partnership with the business based on strategic alignment, business value, and organizational readiness.

(20%) Enterprise Data Platform Architecture, Data Operations, and Governance
Lead the strategy, architecture, development, and operation of the enterprise data platform, including the Enterprise Data Warehouse, Azure Data Lake, Databricks Lakehouse, integration services, and enterprise reporting environments.
Establish enterprise data governance, data quality, metadata management, master data management, and information protection capabilities.
Oversee enterprise data architecture, pipelines, integration patterns, and platform operations, ensuring reliability, scalability, security, compliance, and performance.
Deliver trusted, accessible, and reusable enterprise data products that accelerate analytics delivery and improve business decision-making.
Manage enterprise analytics platforms and visualization technologies, including Power BI and cloud-based analytics services.
Drive enterprise data democratization through secure, governed self-service access to trusted data and business insights.

(20%) Advanced Analytics, AI & Intelligent Decision Support
Develop enterprise analytics capabilities that improve decision-making, customer outcomes, operational performance, and business growth.
Expand enterprise analytics and AI capabilities—including predictive analytics, machine learning, real-time intelligence, and self-service reporting—to improve decision-making and business outcomes.
Lead enterprise AI strategy, initiatives delivery across machine learning, generative AI, agentic AI, copilots, and intelligent digital capabilities, enabling new ways of working and to create business value.
Partner with business leaders to identify, prioritize, and scale high-value AI use cases across customer, dealer, employee, and enterprise operations.
Establish Responsible AI governance, policies, model lifecycle management, and AI risk management practices.
Measure adoption rate, business value, and operational impact of analytics and AI solutions through defined KPIs and value realization metrics.

(20%) Intelligent Automation, Enterprise AI Enablement and Adoption
Execute the enterprise strategy for intelligent automation and AI-enabled business transformation across business and technology functions.
Drive adoption of intelligent automation and AI capabilities, including RPA and AI-powered solutions, to improve productivity, efficiency, and employee experience.
Drive adoption of workflow automation and robotic process automation (RPA). Lead enterprise deployment, governance, and adoption of AI platforms including Microsoft Copilot, Claude, and future enterprise AI capabilities.
Co-own the enterprise AI Workforce Strategy in partnership with Human Resources (HR) , establishing the operating model, governance framework, workforce readiness assessments, role impact analysis, capability-building programs, employee communications and change management required to scale Data/AI adoption responsibility across the enterprise.
Partner with Legal, Security, Risk, and IT to ensure the secure, ethical and compliant deployment and lifecycle management of AI technologies; serve as the technology co-owner alongside HR for all enterprise AI adoption, people readiness and organizational change programs.
Continuously evaluate emerging AI technologies, market trends, and vendor capabilities, translating innovation into scalable business solutions that create competitive advantage.
Establish shared metrics and governance with HR to track AI adoption rates, workforce capability growth, employee experience impact, and value realization across all AI enablement programs.

(20%) Organizational Leadership & Operational Excellence
Sets strategic direction across multiple departments and broad functions, aligning team priorities with enterprise objectives to drive cohesive execution.
Build, lead, and develop a high-performing organization of data architects, engineers, analysts, data scientists, AI engineers, automation specialists, product owners, and technical leaders.
Lead relationships with strategic data platform vendors, 3rd party data providers, and partners, including contracts, licensing, and technical delivery.
Establish operating models, delivery frameworks, engineering standards, prod