VP, Data Strategy & Governance

Humana•Louisville, TX

14h

About The Position

The Vice President, Data Strategy & Governance is a senior executive accountable for defining, advancing, and operationalizing the enterprise data strategy. The role leads the full lifecycle of data governance, including policy design, sensitive data management, technology enablement, data quality, and regulatory compliance. As a strategic advisor to executive stakeholders across business units and technology functions, the VP partners with Cybersecurity, Enterprise Architecture, and business leaders to cultivate a trusted, high-quality, accountable, data-rich, AI-ready environment. The VP builds and develops a high-performing data governance organization, shapes enterprise data culture, and influences enterprise-wide change. The role promotes a data product operating model, embedding accountability for data quality, metadata, lineage, access, and lifecycle management across the enterprise. It applies data governance, data protection, emerging ML/AI-based governance tools, and knowledge of legislation covering personal and sensitive data to enable digital and analytics goals while strengthening cyber-breach resistance. The position establishes the enterprise data strategy and roadmap; leads governance of data programs and investment priorities; builds teams and data literacy; selects and implements governance technologies; improves governance processes and self-service access; and leads data risk, privacy, and compliance programs. The role provides recurring executive and Board-level reporting on governance risk, compliance, and program maturity.

Requirements

10+ years of senior leadership experience in data governance, data management, or data strategy roles in large, complex, matrixed corporate environments.
10+ years of hands-on data governance experience in on-premises and cloud-native environments, such as AWS, Azure, or GCP.
Demonstrated success building and scaling data governance programs from concept through enterprise adoption, with measurable improvements in data quality, compliance, and business outcomes.
Experience managing and delivering large, multi-workstream programs, including strategic initiatives, technology implementations, and organizational transformation, on time and within budget.
Hands-on experience and/or leadership responsibility for technical data governance tools, including data catalogs, lineage platforms, data marketplaces, and data quality frameworks.
Deep expertise in data architecture, data warehousing, data quality processes, and enterprise data modeling.
Experience with data protection strategies, including encryption, tokenization, data masking, data loss prevention, and role-based access control design.
Working knowledge of cybersecurity assessment methodologies and data security controls, with experience partnering with CISO and Security/Enterprise Architecture functions.
Familiarity with ML/AI-based data governance approaches, including automated metadata tagging, anomaly detection, synthetic data generation, and differential privacy.
Strong command of data privacy regulations, including HIPAA, CCPA/CPRA, GDPR, and related legislative frameworks.
Ability to champion an enterprise data product mindset, manage data products through their lifecycle, and maximize business value, adoption, quality, and reuse.
Exceptional executive presence and communication skills, including the ability to explain complex data concepts to C-suite, Board, and business stakeholders.
Evidence of introducing emerging technologies and developing analytics-based capabilities while maintaining cost awareness and commercial strategy.
Proven ability to drive enterprise-wide change in matrixed organizations through influence, coalition-building, and stakeholder management without direct authority.
Advanced degree (Master's or higher) in Computer Science, Data Science, Information Management, Statistics, Mathematics, Law, Cybersecurity, or a related field.
40 scheduled weekly hours.

Nice To Haves

Experience in consumer goods, healthcare, financial services, or technology industries is strongly preferred.
A Ph.D. in a relevant discipline or an MBA is a significant additional asset.
Dual degrees combining technical and business or legal disciplines are highly valued.
Relevant professional certifications such as CDMP, CIPP, CISM, CISSP, or cloud data platform certifications are a plus.

Responsibilities

Establish and own the enterprise data strategy, translating organizational goals into an evolving roadmap spanning people, process, technology, and budget.
Lead portfolio governance of enterprise data programs, prioritizing and resourcing initiatives and ensuring measurable business outcomes aligned with financial and strategic objectives.
Partner with the Chief Data & Analytics Officer and executive peers to communicate the value of data assets, influence investment decisions, and embed data thinking into enterprise planning.
Ensure foundational data infrastructure, lineage, quality, and accessibility support enterprise data science, AI, and generative AI use cases.
Develop a data product mindset and promote reusable, trusted, well-documented data assets across business units.
Build, lead, and develop a high-performing team across sensitive data governance, lineage and mapping, enrichment, quality, democratization, and program management.
Foster accountability, innovation, and continuous learning; champion data literacy and broader access to trusted data.
Recruit and develop diverse senior talent, establish career pathways, and mentor future data leaders.
Build relationships across Technology, Cybersecurity, Legal, Compliance, Finance, and business units to drive governance adoption.
Define team operating models, performance metrics, and OKRs demonstrating strategic and financial impact.
Evaluate, select, and implement enterprise data governance platforms, data catalogs and marketplaces, data quality tools, and metadata management systems.
Modernize data scanning, automated tagging, and labeling to improve classification, governance efficiency, and data loss prevention outcomes.
Partner with Security Architecture and Enterprise Architecture to deploy integrated data governance and security solutions on-premises and in cloud environments.
Operationalize ML/AI-based governance approaches, including automated lineage discovery, anomaly detection, synthetic data generation, and differential privacy.
Maintain awareness of governance technologies and drive a buy/build/partner strategy balancing innovation, cost discipline, and commercial accountability.
Enhance enterprise governance capabilities, including metadata management, lineage, data quality standards, master data management, and access governance, through a measurable roadmap.
Define, publish, and enforce enterprise data policies, standards, and controls for consistent, compliant, high-quality data use.
Enable self-service data access through governance guardrails, role-based access controls, and data marketplace infrastructure.
Establish stewardship programs and data domain ownership models that distribute accountability for data quality and governance.
Improve anonymization, de-identification, and synthetic data capabilities to enable analytics while protecting sensitive information.
Lead the enterprise Data Risk Assessment program, identifying, measuring, and managing data security risks across applications, platforms, and business and technology initiatives.
Ensure data practices comply with applicable privacy regulations and industry standards, including HIPAA, CCPA/CPRA, and GDPR.
Collaborate with Legal, Compliance, and Cybersecurity to assess regulatory changes and implement appropriate controls before compliance deadlines.
Strengthen data protection through encryption, tokenization, data masking, data loss prevention, and access control frameworks.
Provide recurring executive and Board-level reporting on data governance risk posture, compliance status, and program maturity.
Translate complex data concepts into clear communications for C-suite, Board, and business stakeholders.
Drive enterprise-wide change in matrixed organizations through influence, coalition-building, and stakeholder management.