Principal Data and Ontology Architect - AI Enablement

Job Purpose

• The AI Data & Ontology Enablement Lead will support the implementation and adoption of data and ontology enablement practices and standards within Control Tower Operations to support scalable, governed, and business‑aligned AI initiatives.
• Will serve as the primary bridge between Business Units, Global IT, and Control Tower Operations.
• This role ensures shared understanding of data practices, workflows, and requirements by helping to translate established Global IT standards and operating models into repeatable guidance for Business Units and data stewards, while representing business domain needs back to IT.
• Through data steward education, workflow establishment, and close alignment with Control Tower governance processes, this role prevents fragmented, one‑off data requests and ensures AI initiatives are supported by trusted data, shared meaning, and sustainable enterprise operations.

• Enterprise Ontology Strategy & Enablement:
  • Support the implementation and ongoing maintenance of ontology enablement practices and operating model strategy to support AI, analytics, and digital initiatives across multiple Business Units.
  • Apply established standards for semantic modeling, domain alignment, concept reuse, and ontology lifecycle management.
  • Serve as the enterprise subject‑matter authority for ontology‑related topics, providing recommendations and guidance to governance and leadership forums.
  • Collaborate with Global IT and enterprise data architecture, to help ensure ontology practices align with enterprise data platforms and Control Tower operational processes.
• Business Unit Data & Ontology Enablement:
  • Partner with Business Units to understand domain concepts, terminology, operational data, and AI use cases, translating them into ontology‑aligned data structures.
  • Guide Business Units in contributing domain models, metadata, and data assets into the enterprise ontology using defined governance and intake processes.
  • Enable repeatable onboarding of Business Unit data into AI initiatives, reducing reliance on ad‑hoc IT engagement and minimizing duplicated effort.
  • Provide input on prioritization of ontology enhancements based on organizational goals, AI roadmap needs, and enterprise value.
• Global IT Bridge & Translation:
  • Serve as a liaison between Business Units and Global IT for AI data and ontology‑related matters.
  • Engage with Global IT teams to understand enterprise data platforms, workflows, standards, and operational constraints.
  • Translate Global IT practices, requirements, and workflows into clear, actionable guidance for Business Unit data stewards.
  • Represent Business Unit data and ontology needs back to Global IT to inform platform evolution, tooling, and process improvements.
  • Prevent fragmented, one‑by‑one data requests by establishing shared understanding and standardized engagement models.
• Data Enablement & Workflow Establishment:
  • Educate, guide, and support Business Unit data stewards on their roles in data governance, ontology contribution, and AI data enablement.
  • Support the development and documentation of workflows, expectations, and operating models for how BU data stewards engage with the Control Tower and Global IT.
  • Ensure Business Unit Data Stewards understand how to prepare, govern, and submit data assets for ontology integration and AI use.
  • Promote consistent adoption of governance, quality, and semantic standards across Business Units.

• Control Tower Operations Alignment:
  • Support integration of data and ontology enablement into Control Tower workflows.
  • Provide operational insight into data readiness, semantic risks, and governance gaps to inform Control Tower decision‑making.
  • Identify systemic issues and contribute recommendations to drive continuous improvement of data enablement processes.
  • Assist teams in improving understanding and utilization of data in AI processes.
• Semantic Integrity, Data Quality &
  
  Risk Management:
  • Ensure semantic integrity, data quality, lineage, and consistency are maintained as data assets flow into AI solutions.
  • Identify systemic issues and recommend continuous improvement opportunities to Control Tower Operations…