Vice President, AI & Data Engineering

The Big Picture

We are at an inflection point. We have ambitious AI and machine learning goals, a talented but early-stage team, and data infrastructure that needs to mature in order to fully unlock those ambitions. This role exists to close that gap.

Day To Day

• Define and execute the enterprise AI and data engineering roadmap across our multi-brand portfolio, translating CEO vision into a concrete, phased build plan.
• Lead the maturation of our data architecture on Azure — including evaluation and implementation of a modern data platform (Snowflake or Databricks) — to create the infrastructure foundation that AI and ML initiatives require.
• Direct and mentor AI engineers, providing the technical leadership, structure, and growth opportunities.
• Oversee the data engineering team, setting standards, priorities, and quality expectations.
• Identify, evaluate, and implement AI and ML use cases across customer experience, operations, and revenue — including personalization, demand forecasting, and predictive analytics.
• Own vendor relationships, tool selection, and technology investments for the AI and data engineering stack.
• Champion AI adoption and governance across the enterprise, including stewardship of AI tools such as Claude Enterprise.
• Establish data governance, security, and privacy standards in partnership with IT and Legal leadership, aligned to Azure cloud compliance requirements.
• Serve as a trusted thought partner to the CEO and senior leadership, proactively surfacing high-value opportunities where AI and data can drive efficiency and growth.

Experience

• 10+ years of progressive experience in data engineering, data science, or AI/ML, with at least 5 years in a senior leadership role.
• Demonstrated track record of standing up AI and ML capability from scratch — ideally within a mid-market, multi-brand, or similarly resource-constrained organization.
• Proven experience managing and growing junior technical talent into high performers.
• Experience leading data architecture modernization, including cloud migrations and modern data platform implementation.