Sr. Director, AI-Ready Data Governance

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands. About the Role At Veeam Software, we’re on a mission to become a truly AI-powered organization, and trusted data is at the core of that transformation. As the The Senior Director of AI ‑ Ready Data Governance owns the company ‑ wide mandate to ensure Veeam ’ s data is trusted, governed, and ready to power AI at scale. Building on core data management foundations, this role extends governance to AI agents, models, and sources of trust , ensuring AI products, insights, and decisions are safe, explainable, and reliable. Operating with visibility to the COO, CIO, and SVP leadership, this role ensures data governance is no longer a back ‑ office function, but a strategic enabler of Veeam ’ s ambition to become an AI ‑ powered company. What You’ll Do Own and evolve enterprise data governance to ensure data is reliable, explainable, and fit for AI consumption, not just analytics or reporting. Establish clear standards for data definitions, ownership, quality, lineage, and access across core domains (e.g., Account, Customer, Product, ARR, Employee). Define and enforce clear data quality thresholds required before data can be used by AI systems, including accuracy, completeness, timeliness, and consistency. Create explicit “AI ‑ approved ” vs. “ not AI ‑ ready ” data classifications to remove ambiguity for AI and internal AI product teams. Certify authoritative datasets, metrics, and definitions that AI agents, models, and analytics must use. Actively reduce duplicate, unofficial, or unmanaged datasets that lead to conflicting answers, model drift, and loss of trust. Extend data governance beyond tables and dashboards to AI agents, features, and models, ensuring clarity on what data they use, how it is transformed, and where accountability sits. Maintain end ‑ to ‑ end data lineage from source systems through transformations to AI outputs. Work closely with Data Science, AI, and Sales AI teams to embed governance into AI design and delivery, rather than bolting it on after the fact. Serve as the primary data governance partner to Security, Legal, Privacy, and Risk, ensuring AI data usage aligns with regulatory, contractual, and customer commitments. Treat AI data inputs as living assets, continuously monitoring for drift, degradation, misuse, or changing business context as AI adoption scales. What You’ll Bring Proven experience leading data governance, data management, or data platform initiatives in a SaaS or enterprise environment Strong understanding of how data supports AI/ML systems and data-driven decision-making Experience building and scaling enterprise data governance frameworks Solid foundation in data quality, lineage, and metadata management Ability to balance strategic vision with hands-on execution Experience working cross-functionally with both technical and business stakeholders Strong communication and leadership skills, with the ability to influence at all levels of the organization Bonus Skills Experience working on or supporting AI-driven products or platforms Background in data architecture, data engineering, or analytics engineering Familiarity with AI governance, explainability, or responsible AI practices Experience in high-growth SaaS or cloud environments Advanced degree in a relevant field What you'll get ... (truncated, view full listing at source)