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The Vice President, Data Strategy & Governance is a senior executive accountable for defining, advancing, and operationalizing the enterprise data strategy. This leader drives the full lifecycle of data governance — from policy design and sensitive data management to technology enablement, data quality, and regulatory compliance. Serving as a strategic advisor to executive stakeholders across all business units and technology functions, the VP partners closely with Cybersecurity,
Enterprise Architecture, and line-of-business leaders cultivate a data-rich, AI-ready environment grounded in trust, quality, and accountability.
The VP is a visionary organizational builder who attracts and develops world-class talent, shapes data culture, and influences enterprise-wide change. This individual would need to partner across business and technology leaders to drive a product mindset and promote adoption to realize business outcomes. This leader will promote a data product operating model by embedding accountability for data quality, metadata, lineage, access, and data lifecycle management across the enterprise. This leader brings deep command of applied data governance practices, data protection strategies, emerging ML/AI-based governance tools, and the legislative landscape governing personal and sensitive data. Their work directly enables the organization's digital and analytics ambitions while fortifying its cyber-breach resistance posture. Key Responsibilities
Strategic Initiatives & Program Outcomes
Establish and own the enterprise data strategy, translating organizational goals into a continuously evolving roadmap of data capabilities spanning people, process, technology, and budget.
Lead portfolio governance of enterprise data programs, ensuring initiatives are prioritized, resourced, and delivering measurable business outcomes aligned to financial and strategic objectives.
Partner with the Chief Data & Analytics Officer and executive peers to articulate the value of data assets, influence investment decisions, and embed data thinking into enterprise planning cycles.
Drive enterprise-scale data science and AI readiness by ensuring foundational data infrastructure, lineage, quality, and accessibility meet the demands of advanced analytics and generative AI use cases.
Develop and maintain a data product mindset across the organization — enabling reusable, trusted, and well-documented data assets that accelerate time-to-insight across business units.
Team Building & Organizational Development
Build, lead, and continuously develop a high-performing, world-class team of experts spanning sensitive data governance, data lineage and mapping, data enrichment, data quality, data democratization, and program management.
Foster a culture of accountability, innovation, and continuous learning; champion data literacy initiatives that upskill the broader organization and democratize access to trusted data.
Act as a Culture Shaper and Talent Builder — recruiting diverse, senior talent, establishing clear career pathways, and mentoring future data leaders across the enterprise.
Operate as a cross-functional influencer and collaborator, building strong relationships across Technology, Cybersecurity, Legal, Compliance, Finance, and business unit stakeholders to drive data governance adoption at scale.
Define team operating models, performance metrics, and OKRs that demonstrate the strategic and financial impact of the data governance function.
Technology Implementations & Tools
Lead evaluation, selection, and implementation of enterprise data governance platforms, data catalog and marketplace solutions, data quality tooling, and metadata management systems.
Modernize data scanning, automated tagging, and labeling capabilities to improve governance efficiency, enable proactive data classification, and strengthen data loss prevention (DLP) outcomes.
Partner with Security Architecture and Enterprise Architecture to design and deploy solutions that deliver integrated data governance and data security at scale — on-premises and across cloud environments.
Invest in and operationalize innovative ML/AI-based approaches for data governance, including automated lineage discovery, anomaly detection, synthetic data generation, and differential privacy techniques.
Maintain awareness of the evolving data governance technology landscape; drive a buy/build/partner strategy that balances innovation with cost discipline and commercial accountability.
Data Governance Process Improvements
Operate and continuously enhance enterprise data governance capabilities — including metadata management, data lineage, data quality standards, master data management, and access governance — through a structured and measurable capability roadmap.
Define, publish, and enforce enterprise data policies, standards, and controls ensuring consistent, compliant, and high-quality data usage across all business domains.
Champion data democratization by enabling self-service data access models backed by robust governance guardrails, role-based access controls, and data marketplace infrastructure.
Establish data stewardship programs and data domain ownership models that distribute accountability for data quality and governance across the enterprise.
Drive continuous improvement of data anonymization, de-identification, and synthetic data capabilities to enable broader analytics use while protecting sensitive information.
Risk Management & Compliance
Lead the enterprise Data Risk Assessment program, identifying, measuring, and managing data security risks across applications, platforms, and business and technology initiatives.
Ensure the organization's data practices comply with applicable data privacy regulations and industry standards, including HIPAA, CCPA/CPRA, GDPR, and other relevant legislation governing personal and sensitive data.
Collaborate with Legal, Compliance, and Cybersecurity to proactively identify regulatory changes, assess their data governance implications, and implement controls before compliance deadlines.
Strengthen data protection strategy and execution — including encryption, tokenization, data masking, data loss prevention, and access control frameworks — to improve cyber-breach resistance.
Provide executive reporting and Board-level transparency on data governance risk posture, compliance status, and program maturity metrics on a recurring basis.
Use your skills to make an impact
Key Requirements
Experience
10+ years of senior leadership experience in data governance, data management, or data strategy roles within large, complex, matrixed corporate environments.
10+ years of hands-on data governance experience, including both on-premises and cloud-native environments (AWS, Azure, GCP or equivalent).
Demonstrated track record of building and scaling data governance programs from concept through enterprise adoption, with measurable improvements in data quality, compliance, and business outcomes.
Proven experience managing and delivering large, multi-workstream programs — including strategic initiatives, technology implementations, and organizational transformation — on time and within budget.
Prior hands-on experience and/or leadership responsibility for technical data governance tools, including data catalogs, data lineage platforms, data marketplace systems, and data quality frameworks.
Relevant experience in consumer goods, healthcare, financial services, or technology industries strongly preferred.
Technical & Domain Knowledge
Deep expertise in data architecture, data warehousing, data quality processes, and enterprise data modeling.
Relevant 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.
Champion and drive a product mindset across the enterprise data and analytics, treat data as a strategic asset and managing data products through their full lifecycle to maximize business value, adoption, quality and reuse.
Leadership & Influence
A visionary Culture Shaper, Talent Builder, Results Driver, Systems Thinker, and Accountability Partner who engages and aligns the broad enterprise toward common data goals.
Exceptional executive presence and communication skills; able to translate complex data concepts into clear, compelling narratives for C-suite, Board, and business stakeholders.
Strong evidence of the ability to introduce emerging technologies and develop 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.
Leadership Competencies
Culture Shaper
Actively builds an inclusive, high-trust data culture. Champions data literacy, promotes ethical data use, and sets behavioral expectations that reinforce accountability and transparency.
Talent Builder
Recruits, develops, and retains diverse, world-class talent. Creates clear career pathways, coaches emerging leaders, and builds bench strength across the data governance organization.
Results Driver
Sets ambitious goals and holds self and team accountable. Translates strategy into executable plans, tracks progress with rigor, and delivers measurable financial and operational impact.
Systems Thinker
Understands interconnections across data, technology, process, and people. Designs holistic governance frameworks that scale and anticipate second-order effects on the enterprise.
Influential Collaborator
Builds trust and credibility across business and technology functions. Uses data to persuade, aligns diverse stakeholders around shared priorities, and navigates complex political dynamics with integrity.
Strategic Innovator
Brings intellectual curiosity and market awareness. Proactively identifies emerging technologies and governance practices, translating external trends into competitive organizational advantage.
Education Advanced degree (Master's or higher) in Computer Science, Data Science, Information Management, Statistics, Mathematics, Law, Cybersecurity, or a related field required.
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 (e.g., CDMP, CIPP, CISM, CISSP, or cloud data platform certifications) are a plus.
Scheduled Weekly Hours 40
About us
About Humana : Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana .com and at CenterWell.com.
Equal Opportunity Employer
It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
