At ALSAC you do more than make a living; you make a difference.

The Sr. Director, Data Governance & Enablement leads the enterprise program that makes trusted, responsible, and privacy-centered use of data possible at scale. This leader establishes ownership, quality expectations, access, accountability, lifecycle management, retention, acceptable use, compliance, sharing, and integration across the organization’s data.

The role creates the operating model, decision rights, policies, standards, and controls that allow the organization to create value from data while protecting constituent, donor, employee, and organizational information. It integrates enterprise data governance, data enablement, and operational privacy into a cohesive program that supports innovation, strengthens trust, and manages enterprise risk. Its scope extends to 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 the appropriate enterprise partners.

The Sr. Director directs the operational privacy program within Enterprise Data & Intelligence and translates legal, regulatory, ethical, and organizational expectations into practical data practices, system requirements, review processes, and measurable controls. Working closely with Legal, Information Security, Technology, Procurement, Risk, and business leaders, this role helps ensure that privacy is considered from strategy and design through collection, use, sharing, retention, and disposition.

The leader also guides a federated community of data owners, product owners, stewards, analysts, and technology partners. Through this community, the role creates clear accountability for data quality, metadata, lineage, access, lifecycle, appropriate use, and issue remediation. Governance is designed to operate within business, technology, analytics, and product delivery rather than as a separate or late-stage approval exercise.

Essential Job Functions:

Enterprise Data Governance Strategy and Operating Model

• Develop, execute, and own the enterprise data governance and enablement strategy, roadmap, and maturity plan.
• Establish policies, standards, decision rights, governance forums, and escalation paths, with 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.

Privacy Leadership, Operations and Health Reporting

• Lead the operational privacy program within Enterprise Data & Intelligence in partnership with Legal, Information Security, Technology, Procurement, Risk, and business teams, translating privacy obligations into practical 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, and 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 to guide action and strengthen accountability.

Trusted Data, Quality and Metadata Management

• 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 fitness for purpose, access conditions, privacy requirements, and known limitations.

Data Lifecycle, Access, Retention and Sharing

• 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.
• Ensure exceptions, risk acceptance, and remediation decisions are documented, monitored, and escalated appropriately.

Data Governance for Analytics

• Establish governance requirements for data used in reporting, dashboards, self-service analytics, experimentation, and advanced analytical products, including ownership, quality, lineage, integration, access, acceptable use, sharing, retention, and privacy protection.
• Partner with analytics and business leaders to ensure governed data is fit for its intended purpose and address conflicting definitions, unsupported combinations, incomplete lineage, and inappropriate use of sensitive information.
• Analytical methodology, metric governance, model validation, and interpretation remain with the appropriate analytics owners.

Data Governance for AI and Emerging Uses

• 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.
• This role governs the data used by AI but does not own governance of AI models, applications, algorithms, or enterprise AI lifecycle decisions.

Stewardship, Training and Change Leadership

• Lead a high-performing team and a federated community of data and privacy owners, stewards, analysts, and technology partners, equipping them with clear 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, and measure completion, comprehension, and adoption.
• Influence senior leaders and cross-functional teams to resolve competing priorities, sustain accountability, and embed governance into delivery.

Platforms, Automation and Continuous Improvement

• 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.

Leadership Competencies: The role calls for enterprise thinking, strategic judgment, pragmatic governance, responsible innovation, risk-based decision-making and systems thinking. The leader must be able to build partnerships, navigate conflict, communicate clearly with executives, lead a portfolio and operating model, develop talent and sustain accountability through organizational change.

Required Qualifications:

• Requires a bachelor's degree in information management, data or computer science, analytics, business, risk, law, public policy, or a related field is preferred, with equivalent education and experience considered.
• The successful candidate will bring 10 or more years of progressively responsible experience across data governance, data management, privacy, risk, technology, or related disciplines, including enterprise-scale program leadership, and 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 and 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 the data requirements of machine learning and generative AI.
• Executive communication, facilitation, negotiation, change leadership, and the ability to influence without direct authority are essential.
• Ability to connect governance and privacy investments to growth, efficiency, trust, risk reduction, and strategic outcomes.

Preferred Qualifications:

• 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 are valuable.
• Experience in a mission-driven, fundraising, consumer, healthcare-adjacent, or highly regulated environment is beneficial.

Location: This position is based in Memphis, TN and follows a hybrid work schedule. Remote consideration may be available for qualified candidates located within the United States.

Benefits & Perks

The following Benefits & Perks apply to Full-Time Roles Only.

We’re dedicated to ensuring children and their families have every opportunity to enjoy life’s special moments. We’re also committed to giving our staff excellent benefits so they can do the same.

• Core Medical Coverage: (low cost low deductible Medical, Dental, and Vison Insurance plans)​
• 401K Retirement Plan with 7% Employer Contribution
• Exceptional Paid Time Off
• Maternity / Paternity Leave
• Infertility Treatment Program
• Adoption Assistance
• Education Assistance
• Enterprise Learning and Development
• And more

ALSAC is an equal employment opportunity employer. 

ALSAC does not discriminate against any individual with regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, transgender status, disability, veteran status, genetic information or other protected status.

No Search Firms:

ALSAC does not accept unsolicited assistance from search firms for employment opportunities.  All resumes submitted by search firms to any ALSAC employee or ALSAC representative via email, the internet or in any form and/or method without being contacted and approved by our Employee Experience team and without a valid written search agreement in place will result in no fee being paid if a referred candidate is hired by ALSAC.