Job Requirements Lead Data Governance Specialist The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, data analytics, and scientific approaches such as optimization and statistical modeling to build innovative tools that shape business decisions across The Walt Disney Company. We support Disney Entertainment (ABC, The Walt Disney Studios, Disney+, Hulu), ESPN, Disney Experiences (Theme Parks, Cruise Line, Consumer Products, DVC), and Corporate Finance with strategic applications that enable data-driven decision-making. This team works in office. What You Will Do As the Lead Data Governance Specialist, you will own the data governance craft for our team: the operating model, policies, standards, and stewardship practices that make Disney's data trusted, well described, properly protected, and genuinely easy to use. You will work closely with Data Engineering, Architecture, the Ontology/Semantic Librarian, Security, Privacy, and Legal to see them applied.
Your time will be split roughly evenly across two mandates:
Project Initiatives Projects that focus on unifying data and accelerating access to it across The Walt Disney Company. You will own the governance workstream that makes unified data safe to share and reuse at pace. Lead the development, adoption, and enforcement of the data governance policies, standards, and best practices that span the Data Unification Accelerators program, including the operating model and decision rights that let data be shared and reused safely at speed. Design governance guardrails that accelerate delivery rather than gate it: documented data ownership, pre-agreed classification and data sharing rules, reusable approval paths, and templates that delivery teams can self-serve. Define the metadata, glossary, lineage, and cataloging standards that make unified data discoverable and explainable - business definitions, critical data elements, ownership attributes, and provenance - partnering with the Ontology/Semantic Librarian so that business meaning, ownership, and governance attributes stay aligned with the semantic layer. Set and operate data quality standards for unified data assets: quality dimensions, measurable rules for critical data elements, profiling and scorecards, issue triage, and clear remediation ownership. Shape the governance of the internal Data Marketplace by defining what a data product must satisfy before it is offered to the enterprise - publishing and documentation standards, certification criteria, access and entitlement models, and usage terms. Partner with Security, Privacy, Legal, and the Data Engineering teams to translate privacy, residency, and regulatory obligations into practical, implementable requirements - data classification and sensitivity tiering, role- and attribute-based access, masking, and retention - and assure that those requirements are met. Establish the governance that allows analytics and AI to consume unified data responsibly: approved use, data provenance and attribution, human accountability, and the controls that underpin responsible AI. Define and report the program's governance metrics, maturity measures, risks, and compliance posture to program leadership and enterprise governance forums. Divisional Data Governance Design, Advisory, and Delivery The data governance voice for our division, covering both the design of the capability and the hands-on delivery of it. Act as the division's trusted data governance advisor - the person teams come to for a clear answer on data ownership, classification, sharing, quality, retention, and acceptable use. Design and stand up the divisional governance operating model: data owners and stewards, governance forums and councils, charters, decision rights, RACI, and escalation paths that fit how our teams genuinely work. Author, socialize, and maintain divisional data policies, standards, and procedures, together with the exception and waiver process that sits behind them, keeping all of it aligned to enterprise and corporate policy and current as data protection and AI regulation evolves. Run governance-by-design reviews of new solutions, data products, and third-party or vendor data arrangements, giving teams practical requirements early rather than audit findings late. Deliver governance outcomes hands-on for priority data domains: populate the catalog and business glossary, assign and confirm ownership, stand up quality monitoring, and close the gaps you find. Own the divisional data issue and risk register end to end - intake, root cause analysis, remediation planning, and tracking to closure - and support internal audit, external audit, and regulatory requests. Run access governance for divisional data, including entitlement design, request and approval workflow, periodic access reviews, and least-privilege recertification. Build data literacy and governance capability through training, onboarding material, office hours, and a steward community of practice, and drive the adoption and behavior change that make governance stick. Assess governance maturity, build and sequence a prioritized governance roadmap, and report progress, value, and risk to divisional and senior leadership. Required Qualifications & Skills 7+ years of experience in data roles with significant experience in data and information governance with a focus on enterprise-scale initiatives, including ownership of a governance framework end to end rather than contribution to someone else's. Deep expertise across the core data governance disciplines: operating models and decision rights, policies and standards, data ownership and stewardship, metadata management and business glossary, data quality, data classification, and data lifecycle and retention. Demonstrated experience designing and standing up a data governance operating model - councils and forums, charters, data owner and steward networks, RACI, and escalation - and authoring the policies, standards, procedures, and exception and issue-remediation processes that make it operable and adopted. Strong data quality management experience: defining dimensions and rules for critical data elements, profiling and measurement, scorecards and service levels, root cause analysis, and driving remediation through to closure. Practical working knowledge of data privacy, data protection, and compliance requirements in large enterprises (such as GDPR, CCPA/CPRA, COPPA, PCI DSS, and SOX) and of how to translate them into data classification, access, masking, and retention requirements alongside Privacy, Legal, and Security partners. Experience with access and entitlement governance, including role- and attribute-based access models, dynamic masking, request and approval workflows, and periodic access review and recertification. Background in GRC (Governance, Risk, and Compliance) programs, covering risk and control frameworks, control design and evidence, issue management, audit support, and reporting into governance committees. Hands-on experience with data governance tooling across catalog, business glossary, lineage, data quality, and policy enforcement (for example Collibra, Alation, Atlan, Informatica, Microsoft Purview, Immuta, or OneTrust), and with governing data held in modern cloud platforms such as Snowflake and Databricks. Experience governing data used for analytics, machine learning, and Generative AI, covering provenance, approved use, and responsible AI principles. Excellent communication, facilitation, and influencing skills, with a track record of bringing business, engineering, legal, and privacy stakeholders to a shared decision, and the ability to write clearly for both executive and practitioner audiences. Sufficient technical fluency to engage credibly with data engineering, architecture, and semantic modeling teams on data models, access controls, and platform capabilities, without owning the build. Proven ability to run two mandates in parallel - a large cross-company program and a divisional advisory and delivery portfolio - and to prioritize independently in an ambiguous, fast-moving environment. Desired Qualifications Experience leading data governance in large, complex enterprises, preferably in media, entertainment, or hospitality. Governance experience in a federated or multi-domain operating model, such as data mesh or domain-oriented ownership, where authority is shared rather than centralized. Familiarity with industry governance frameworks and standards (DAMA-DMBOK, DCAM, EDM Council, ISO/IEC 38505, NIST Privacy Framework) and experience running a maturity assessment against one of them. Professional certification such as CDMP (DAMA), DCAM, CIPP/E or CIPM (IAPP), CISA, or CISM. Experience governing data products and internal data marketplaces, including data contracts, certification, and usage terms. Experience of master data and reference data management governance. Experience with records management and retention schedules, and with privacy operations such as data subject access requests, consent, and data minimization. Awareness of semantic technologies - ontologies, taxonomies, knowledge graphs, and semantic layers - and of how governance metadata, ownership, and quality rules attach to them. Experience of responsible AI or AI governance programs, including model and use-case inventories and review processes under emerging AI regulation. Working SQL skills, or the ability to read a data model and profile data, sufficient to validate quality findings and ask sharper questions of engineering teams. Required Education Bachelor's degree and/or equivalent work experience Preferred Education Master's degree and/or equivalent work experience
Disclaimer
PAY TRANSPARENCY
The hiring range for this position in Lake Buena Vista, FL is $137,200 to $184,000 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
This position is with Disney Worldwide Services, Inc., which is part of a business we call The Walt Disney Company (Corporate). To learn more about Disney's guidelines on the use of AI for candidates, click here. Disney Worldwide Services, Inc. is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world.
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