Vp Jobs

About The Position

Requirements

• 10+ years of senior leadership experience in data governance, data management, or data strategy within 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.
• Proven 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 data governance tools, including data catalogs, data 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, including 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 a product mindset across enterprise data and analytics, treating data as a strategic asset and managing data products through their lifecycle to maximize 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.
• Demonstrated leadership capabilities in culture shaping, talent development, results delivery, systems thinking, collaboration, and strategic innovation.

Nice To Haves

• Relevant experience in consumer goods, healthcare, financial services, or technology industries.
• Ph.D. in a relevant discipline or an MBA.
• Dual degrees combining technical and business or legal disciplines.
• Professional certifications such as CDMP, CIPP, CISM, CISSP, or cloud data platform certifications.

Responsibilities

• Establish and own the enterprise data strategy, translating organizational goals into a continuously evolving roadmap covering people, process, technology, and budget.
• Lead portfolio governance of enterprise data programs, ensuring initiatives are prioritized, resourced, and deliver measurable outcomes aligned with 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 incorporate data into enterprise planning.
• Drive data science and AI readiness by ensuring data infrastructure, lineage, quality, and accessibility support advanced analytics and generative AI use cases.
• Develop a data product mindset and enable reusable, trusted, well-documented data assets across business units.
• Build, lead, and develop a high-performing team covering 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 mentor diverse senior talent, establish career pathways, and develop future data leaders.
• Build cross-functional relationships across Technology, Cybersecurity, Legal, Compliance, Finance, and business units to drive governance adoption.
• Define team operating models, performance metrics, and OKRs that demonstrate the strategic and financial impact of data governance.
• Evaluate, select, and implement data governance platforms, data catalogs and marketplaces, data quality tools, and metadata management systems.
• Modernize data scanning, automated tagging, and labeling to improve classification and data loss prevention outcomes.
• Partner with Security Architecture and Enterprise Architecture to deploy integrated data governance and security solutions across on-premises and 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 cost-conscious, commercially accountable buy/build/partner strategy.
• Continuously enhance metadata management, lineage, data quality standards, master data management, and access governance through a measurable capability roadmap.
• Define, publish, and enforce enterprise data policies, standards, and controls for consistent, compliant, high-quality data usage.
• Enable self-service data access with 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.
• Improve data anonymization, de-identification, and synthetic data capabilities to broaden analytics use while protecting sensitive information.
• Lead the enterprise Data Risk Assessment program across applications, platforms, and business and technology initiatives.
• Ensure data practices comply with applicable privacy regulations and standards, including HIPAA, CCPA/CPRA, and GDPR.
• Collaborate with Legal, Compliance, and Cybersecurity to assess regulatory changes and implement 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.