Director Data Office & AI Readiness

Director Of Data Office & Ai Readiness

The Director of Data Office & AI Readiness will build and lead an enterprise Data Office that establishes trusted, durable, and business-ready data across priority initiatives and core domains. The incumbent will be both strategic and execution-oriented: they will drive results for priority programs while building the long-term capabilities required for AI readiness at scale, data reuse, and quality. The Director of Data Office & AI Readiness will stand up and scale an enterprise Data Office, collaborating closely with business stakeholders and technology partners to implement robust frameworks, data standards, and stewardship practices.

The incumbent will manage enterprise data portfolio intake, prioritization, and sequencing of high-value data initiatives, ensuring alignment to strategic business goals and maximizing value delivery.

Principal Responsibilities:

• Establishes and leads the Data Office as a formal enterprise capability with a clear charter, operating model, defined ownership and accountability, escalation paths, and measurable business outcomes.
• Defines roles, responsibilities, and engagement models across domain owners, stewards, and IT partners to support business-led data accountability.
• Builds and leads the enterprise data operating model, including governance councils, working teams, and executive forums that prioritize data initiatives, resolve cross-functional issues, inform, and ensure strategic alignment.
• Owns enterprise data demand and portfolio management, orchestrating intake, triage, prioritization, and sequencing the strategic roadmap of data initiatives based on business value, complexity, and reuse.
• Establishes and operationalizes the data ownership and stewardship framework, clarifying accountability for data elements, definitions, business rules, quality, systems of record, access, and usage across domains.
• Drives a value-oriented data roadmap focused on high-impact domains and strategic programs, delivering early governance wins and scaling successful practices across the organization to maximize business impact.
• Leads enterprise data quality and governance practices, including developing standard data definitions, implementing metadata and lineage management, establishing data certification processes, ongoing data quality monitoring, and issue management.
• Collaborates with enterprise architecture and data engineering teams to align modern data platforms and architecture with business needs; ensuring consistent data structures, reusable data assets, and effective lifecycle management.
• Enables AI readiness and self-service analytics by collaboratively defining data management standards, privacy and security guardrails, and consumption models to support analytics, ML and AI initiatives.
• Champions enterprise-wide adoption and cultural change by driving communication, training, stakeholder education and engagement; developing a high-performing team, and fostering a data-driven culture.
• Performs other job-related duties as assigned or apparent.

Knowledge / Skills / Abilities:

• Deep expertise in enterprise data governance, data management principles, data ownership models, and designing business-led data operating models
• Strong command of data quality management, metadata standards, data lineage, data certification, and data governance
• Proven ability to design and implement intake, triage, prioritization, and portfolio management processes for enterprise-wide data initiatives
• Broad understanding of modern cloud-based data architectures (e.g., multi-layer or medallion architectures), data product management, and governed self-service analytics environments
• Working knowledge of data catalog, data quality / observability, and MDM tools in modern cloud environments (e.g., Snowflake, data.world, Accel Data, Reltio)
• Exceptional skill in translating complex data management and governance concepts into clear business terms for executive and non-technical stakeholders
• Strategic mindset with a history of connecting data investments to tangible business value, risk mitigation, efficiency gains, and AI enablement
• Strong leadership and influence skills,…