Sr Director - Data Governance & Enablement (Memphis, TN or Remote in USA)

ALSAC•Memphis, TN

12d•Hybrid

About The Position

The Sr. Director, Data Governance & Enablement leads ALSAC’s enterprise program for trusted, responsible, and privacy-centered use of data. The role establishes ownership, quality expectations, access, accountability, lifecycle management, retention, acceptable use, compliance, sharing, and integration across the organization’s data. It creates the operating model, decision rights, policies, standards, and controls that enable data-driven value while protecting constituent, donor, employee, and organizational information. The role integrates enterprise data governance, data enablement, and operational privacy into a cohesive program. It directs the operational privacy program within Enterprise Data & Intelligence, translating legal, regulatory, ethical, and organizational expectations into practical data practices, system requirements, review processes, and measurable controls. In partnership with Legal, Information Security, Technology, Procurement, Risk, and business leaders, it supports privacy throughout data collection, use, sharing, retention, and disposition. The Sr. Director guides a federated community of data owners, product owners, stewards, analysts, and technology partners, establishing accountability for quality, metadata, lineage, access, lifecycle, appropriate use, and issue remediation. The role covers data used in reporting, analytics, machine learning, and generative AI, while governance of analytical methods, AI models, AI applications, and the broader AI lifecycle remains with appropriate enterprise partners. The position is based in Memphis, Tennessee, with a hybrid schedule. Remote consideration may be available for qualified candidates located within the United States.

Requirements

Bachelor’s degree in information management, data or computer science, analytics, business, risk, law, public policy, or a related field is preferred; equivalent education and experience are considered.
At least 10 years of progressively responsible experience across data governance, data management, privacy, risk, technology, or related disciplines, including enterprise-scale program leadership.
At least five years of experience leading teams, operating models, or federated communities in a complex environment.
Demonstrated experience establishing data governance frameworks, policies, standards, decision rights, and controls.
Experience converting privacy and risk requirements into practical business and technology practices.
Strong understanding of modern data ecosystems, metadata and catalog capabilities, data quality, lineage, cloud platforms, analytics delivery, and data requirements for machine learning and generative AI.
Executive communication, facilitation, negotiation, and change leadership skills, including the ability to influence without direct authority.
Ability to connect governance and privacy investments to growth, efficiency, trust, risk reduction, and strategic outcomes.
Ability to build partnerships, navigate conflict, communicate clearly with executives, lead a portfolio and operating model, develop talent, and sustain accountability through organizational change.

Nice To Haves

Experience leading integrated data governance, enablement, and privacy programs.
Experience with enterprise data catalogs, business glossaries, lineage, data-quality monitoring, governance workflows, or privacy-management capabilities.
Experience establishing controls for data used in analytics, machine learning, or generative AI.
Relevant credentials in data management, privacy, security, risk, analytics, project management, or business process management.
Experience in a mission-driven, fundraising, consumer, healthcare-adjacent, or highly regulated environment.

Responsibilities

Develop, execute, and own the enterprise data governance and enablement strategy, roadmap, and maturity plan.
Establish governance policies, standards, decision rights, forums, escalation paths, and clear accountability for data owners, product owners, stewards, and custodians.
Define measures for adoption, data quality, privacy risk, policy adherence, issue remediation, and value realization.
Lead the operational privacy program with Legal, Information Security, Technology, Procurement, Risk, and business teams, translating privacy obligations into policies, system requirements, review processes, and data controls.
Embed privacy by design across systems, campaigns, products, analytics, AI data use, data exchanges, and third-party services; oversee data minimization, purpose alignment, consent and preferences, retention, data-subject request enablement, incident support, and vendor risk.
Provide recurring operational health reporting on privacy risks, requests, incidents, control performance, policy adherence, third-party concerns, and remediation progress.
Establish enterprise practices for data ownership, quality, access, accountability, classification, metadata, lineage, integration, sharing, acceptable use, compliance, master and reference data, retention, and disposition.
Lead adoption of the enterprise data catalog and glossary, including definitions, critical data elements, ownership, quality expectations, lineage, and certification status.
Create risk-based certification and issue-management practices that communicate data fitness for purpose, access conditions, privacy requirements, and known limitations.
Define and operationalize requirements for data collection, access, use, movement, sharing, retention, archival, and disposition across platforms and business processes.
Partner with business and technology owners to apply proportionate controls to data exchanges, campaigns, data products, marts, and third-party services; document, monitor, and appropriately escalate exceptions, risk acceptance, and remediation decisions.
Establish governance requirements for data used in reporting, dashboards, self-service analytics, experimentation, and advanced analytical products.
Partner with analytics and business leaders to ensure governed data is fit for purpose and address conflicting definitions, unsupported combinations, incomplete lineage, and inappropriate use of sensitive information.
Establish governance requirements for data used in machine learning, generative AI, and emerging technologies, including ownership, provenance, quality, metadata, lineage, access, sharing, retention, acceptable use, and compliance.
Define expectations for training, grounding, reference, and evaluation data, and provide risk-based review for novel uses, sensitive populations, new data combinations, and external providers.
Lead a high-performing team and federated community of data and privacy owners, stewards, analysts, and technology partners, providing responsibilities, decision authority, playbooks, and support.
Oversee role-based training and practical guidance on privacy, data handling, acceptable use, retention, sharing, and data responsibilities for analytics and AI; measure completion, comprehension, and adoption.
Influence senior leaders and cross-functional teams to resolve competing priorities, sustain accountability, and embed governance into delivery.
Partner with ITS and Product teams to embed data governance and privacy requirements into architecture, delivery methods, platforms, and operational workflows.
Advance automation for metadata, lineage, data-quality monitoring, policy enforcement, access review, retention, consent and preference controls, and evidence collection.
Continuously assess program maturity, regulation, technology, and organizational needs to improve controls, reduce manual effort, and prevent late-stage risk discovery.
Connect governance and privacy investments to growth, efficiency, trust, risk reduction, and strategic outcomes.