SVP, Head of Enterprise Data

SVP, Head of Enterprise Data

The SVP, Head of Enterprise Data is a senior technology leader responsible for defining and executing TKO's enterprise-wide data strategy, architecture, governance, and data products that enable TKO's enterprise systems, AI applications, analytics, and digital experiences. This role will own and drive the development of modern data capabilities focused on making data a trusted, accessible, and strategically governed asset across all of TKO's brands and business units.

Reporting directly to the Chief Data, AI & Technology Officer (CADTO), the SVP, Head of Enterprise Data will serve as TKO's authoritative voice on data, setting the standard for how data is engineered, governed, maintained, and consumed across UFC, WWE, P , IMG, and On Location.

This leader will be a collaborative and strategic thinker, will possess deep technical skills and act as a trusted partner to leaders of our business units and other share service functions. The leader who succeeds will build future ready solutions that will reshape the way TKO operates.

Responsibilities

• Data Platform & Infrastructure
• Own and evolve TKO's enterprise data warehouse — cloud infrastructure, ingestion pipelines, and integrations across all brands and source systems (Salesforce, ERP, HRIS, ticketing, Zeta).
• Ensure platform reliability at TKO's operating cadence, including event-day peak loads across WWE, UFC, and On Location.
• Own cloud strategy, cost optimization, and engineering standards.
• Data Governance, Quality & Data Privacy
• Define and operate TKO's enterprise data governance framework — policies, stewardship model, and data quality SLAs.
• Prepare data for monetization and AI consumption: retrieval, transformation and structuring for our Glean/ Enterprise AI tool. Unstructured data (video, audio, transcripts, fan-service logs) will also need to be leveraged.
• Receive and prioritize AI, analytics, and digital data demand through the enterprise governance front door (DTC), so requests route through one shared intake process.
• Serve as TKO's data governance authority in the Data & Technology Committee (TKO's enterprise governance forum for Data & AI strategy and initiatives).
• Master Data Architecture
• Own the master data architecture for TKO's core data domains — specifically, fans, events, commercial partners/customers, vendors and employees — building unified, cross-brand data models for each.
• Define canonical data models, identity resolution logic, and golden record standards across business units.
• Partner with the application teams (marketing technology platforms and business systems) to design the integration strategy in order to activate unified fan data for personalization, marketing, and loyalty programs.
• Data Products & Semantic Layer
• Build TKO's internal data product capability — SLA-backed, documented data assets serving the AI, analytics, and digital product teams.
• Own the enterprise semantic layer and metrics catalogue — the authoritative definitions of common business metrics across all brands.
• Own a prioritized connector and integration roadmap sequenced by use-case value, partnering with AI & Data Transformation so AI and analytics.
• Own the enterprise data catalogue
• Team Leadership
• Attract, develop, and retain world-class data talent; build a culture of engineering quality and governance rigor.
• Manage the Enterprise Data budget with ROI discipline and partner with People + Culture team on data literacy across business units.

Required Experience and Skills

• 15+ years in data engineering, data architecture, or enterprise data management; 5+ years at SVP or VP level.
• Proven track record building enterprise-scale data platforms — architecture, cloud-native infrastructure (AWS, GCP, or Azure), real-time and batch processing.
• Deep expertise in data governance, MDM, and privacy compliance (GDPR, CCPA, PCI) in a multi-brand or multi-jurisdiction environment.
• Experience building unified data models across key domains.
• Strong data architecture background — data modelling, semantic layers, and integration patterns across source systems.
• Demonstrated ability to lead globally distributed teams and manage large budgets in a matrixed environment.
• Bachelor's degree in Computer Science, Data Science, Engineering, or related field.

Preferred Skills

• Experience in sports, live events, entertainment, hospitality or media where fan/customer data is a core business asset.
• Familiarity with Salesforce, SAP, HRIS architectures, and data catalogue platforms (Atlan, Collibra, or similar).
• Exposure to AI/ML data requirements — feature stores, training pipelines — without owning the AI build function.
• Advanced degree (MS or MBA) preferred.