Director of Data & AI

Required Experience8+ years in data, engineering, or related technical roles, with experience leading teams of senior engineers and specialistsStrong expertise across modern data ecosystems, including architecture, transformation, analytics, and reportingExperience designing internal platforms or shared tooling with an emphasis on governance, reliability, and adoptionDemonstrated ownership of critical data assets (metrics, models, semantic layers) with high stakeholder trustAbility to lead across multiple technical domains, including data engineering, analytics engineering, BI, and software developmentStrong prioritization and decision-making skills, along with the ability to clearly communicate technical concepts in business termsA proactive approach to learning and adapting within a rapidly changing technology landscapePreferred ExperienceFamiliarity with modern data tools such as dbt, Fivetran, BigQuery, or comparable technologiesExposure to AI monitoring or evaluation tools (e.g., LangSmith or similar platforms)Experience with BI platforms that incorporate governed semantic layersHands-on use of enterprise AI tools or platforms in production environmentsExperience scaling self-service analytics capabilities for non-technical usersKey ResponsibilitiesEstablish and deliver foundational capabilities such as trusted data pipelines, curated datasets, governed access layers, and initial AI enablement featuresOwn and evolve the organization’s internal AI ecosystem, including shared tooling, reusable workflows, and mechanisms that allow non-technical users to safely leverage AIDrive measurable outcomes tied to business performance—improving access to insights, increasing confidence in reporting, and enabling operational efficiencyWork closely with cross-functional partners (AI, Analytics, IT, Business Systems, and GTM teams) to anticipate needs and design solutions ahead of demandEvaluate and decide when to build internally versus adopt external tools, with a willingness to pivot or replace solutions as neededCommunicate technical decisions clearly in terms of business impact to executive and operational stakeholdersBalance speed and scalability, designing systems that grow with the business without unnecessary complexityProvide clear direction for the platform while remaining adaptable as priorities evolve