Director Data Office & AI Readiness

Republic Services•Phoenix, AZ

7d•Hybrid

About The Position

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.

Requirements

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, AccelData, 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, including stakeholder management, conflict resolution, and change management within large, matrixed organizations
Proven ability to develop and scale data practices, teams, and adoption across an enterprise, balancing strategic vision with pragmatic implementation.
Comfort with ambiguity and a track record of establishing durable, repeatable processes and standards from the ground up.
Demonstrated success in establishing, scaling, or significantly transforming a Data Office, Data Governance program, or similar enterprise data capability.
Extensive experience designing governance operating models, data stewardship frameworks, decision-rights structures, and executive governance forums in large, complex organizations.
Track record of defining and operationalizing critical data elements (CDEs), data definitions, business rules, metadata and lineage management, data quality controls, certification processes, and issue management.
Hands-on experience developing effective intake, prioritization, and data portfolio management processes for large-scale data initiatives tied to business strategy or transformation programs.
History of partnering with architecture, engineering, security, privacy, legal, product, and business teams to define scalable data management practices, controls, and delivery standards.
Experience with modern cloud-based data platforms and governance technologies (e.g., enterprise data catalogs, metadata management and data quality/observability tools, MDM solutions); Snowflake and data.world experience strongly preferred.
Demonstrated ability to enable advanced analytics and AI/ML initiatives through data management practices, ensuring data is prepared, high-quality, and appropriately governed
Exceptional executive communication and influence skills, with a proven ability to drive change and foster a data-driven culture.
10+ years of progressive experience in enterprise data management, data governance, data strategy, analytics, or related data leadership roles.
7+ years of experience leading cross-functional teams, enterprise programs, or data transformation initiatives that span both business and technology functions.

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.