Vice President, Enterprise Data & AI

Job Purpose The Vice President, Enterprise Data & AI is the executive accountable for driving the enterprise-wide execution, adoption, governance, and value realization of TD SYNNEX’s Data & AI strategy. Reporting to the SVP, Digital Innovation & Enterprise Architecture, this leader converts enterprise strategy into delivered outcomes across the Data Platform, AI Factory, Data Governance, Business Intelligence, and AI Enablement functions, and owns the business results those functions produce.

The role carries accountability for the value of the Data & AI portfolio, not only its delivery. It sets the operating model, prioritizes investment, and establishes the governance and responsible AI controls under which AI is deployed globally. The VP partners with business, technology, security, finance, and legal leaders across four regions to align priorities, remove barriers, and accelerate outcomes that improve decision quality, productivity, and financial performance.

Responsibilities

• Own execution of the enterprise Data & AI roadmap, ensuring strategic priorities are delivered consistently across regions, functions, and business units. Approve sequencing and trade-off decisions across speed, quality, risk, and cost, and hold director-level leaders accountable for committed outcomes.
• Own the benefits case for the Data & AI portfolio from investment approval through post-implementation review. Partner with business leaders and Finance to set baselines, agree measurable value targets, embed capabilities into everyday business processes, and report captured value against commitment. Redirect or terminate initiatives that are not realizing committed value.
• Direct the development and operation of the enterprise Data Platform, AI Factory, and related AI capabilities. Set platform roadmap and approve platform investment so the estate remains scalable, secure, reliable, and positioned to support future business needs.
• Own enterprise data governance and responsible AI practice, including the AI use-case approval process. Accountable for data quality and partner with other teams on security, privacy, regulatory compliance, and model risk management being embedded in the design, deployment, and ongoing operation of Data & AI solutions.
• Set priorities, performance measures, governance forums, and execution processes so resources concentrate on the highest-impact initiatives. Monitor progress, escalate and resolve enterprise risks, and provide transparency into delivery commitments and outcomes.
• Own the operating and investment budget for Data & AI, approve expenditure within delegated authority, and lead strategic vendor selection, negotiation, and performance management. Drive unit-cost improvement while sustaining investment in capabilities that create long-term value.
• Build and lead a global organization of directors, managers, and technical professionals. Define the operating model and organizational design, hire and develop director-level leaders, set succession plans for critical roles, and cultivate a culture of accountability, collaboration, and continuous improvement.

Knowledge, Skills And Experience

• 15 Years+ of relevant work experience in in data, AI/ML, engineering, and/or platform leadership roles, with executive-level accountability for delivery outcomes.
• 8+ Years of experience directly managing / supervising employees
• Demonstrated accountability for an operating budget of $5M or greater and an investment portfolio of comparable scale.
• Hands-on familiarity with the Microsoft ecosystem (e.g., Azure Foundry, Microsoft Copilot, Copilot Studio, modern data platforms (e.g., Snowflake, Databricks) and foundational AI models (openAI, Anthropic, etc).
• Experience with FinOps best practices for cloud and AI cost management, charge back and show back models.
• Proven record of delivering measurable business value from data and AI investments, evidenced by quantified outcomes.
• Deep working knowledge of modern data platform architecture, AI and generative AI deployment at scale, and data governance frameworks.
• Experience establishing responsible AI and data governance practice in a regulated, multi-jurisdiction environment.
• Ability to bridge communication gaps and drive cross-functional alignment to deliver value without conflicting implementations.
• Executive presence and demonstrated effectiveness influencing C-suite peers and reporting to board-level audiences.
• Exper…