VP of Data

Wolfe is a FinTech company embedding AI across its products, operations, and everyday decision-making, and the quality of every AI answer depends on trusted information reaching the right person or agent at the right time.

As VP of Data, you are the directly responsible individual for Wolfe's trusted data supply chain, owning how information is governed, moved, trusted, protected, and made available across employees, AI agents, and business systems.

You will build the Wolfe-specific controls and governance foundation that make Wolfe's data platforms safe, trusted, and valuable, supporting Wolfe's strategy to establish trusted data, ownership, permissions, and governance before scaling AI adoption further.

This is a flat organization, and the Senior Director and Data Engineering team report directly to you; like other senior leaders at Wolfe, you are expected to stay hands-on and contribute to architecture, design, and production code.

This is a 5-day onsite role in Pittsburgh, PA.

Responsibilities:

• Build and operate trusted data pipelines that carry ownership, permissions, lineage, freshness, and auditability from source systems to employees, AI agents, and business processes.
• Establish standards for onboarding, governing, certifying, and retiring information sources, and define authoritative sources with clear ownership, stewardship, and review cycles.
• Create frameworks for information quality, freshness, conflict resolution, and trust scoring so critical information stays trusted, current, and AI-ready.
• Partner with AI, Engineering, and Security teams to ensure AI systems use approved information, setting standards for source attribution, answer quality, unsupported-answer handling, and access governance.
• Directly manage the Senior Director and Data Engineering team, building clear ownership, accountability, and operating rhythms while recruiting, developing, and retaining top talent.
• Define and monitor metrics for trusted source coverage, data quality and freshness, pipeline reliability, permission compliance, answer quality, and source onboarding speed.

Impact Statement:

For more clarity on the role, below are the success metrics and measurements for this role in the first 90 to 120 days.:

• 95% of priority Wolfe data sources have an identified owner, approval status, and review cycle.
• A repeatable governance framework is operating for source onboarding, certification, ownership, review, and retirement, with 95% of priority information flowing through governed pipelines that preserve permissions, ownership, lineage, and auditability.
• A trust framework is live with reporting on source ownership, quality, freshness, approval status, and trust scores, and testing confirms approved users receive approved information while unauthorized users do not.
• Priority AI use cases consume approved, governed, and trusted information sources with measurable answer quality.

Qualifications:

• 12 years leading data, knowledge, governance, or data engineering organizations, including 5 years in a senior leadership role owning people, budgets, and strategy.
• Hands-on technical leader with a track record of building production data platforms and pipelines, and staying close to architecture, design, and code.
• Deep expertise in data governance, metadata, stewardship, lineage, data quality, and information lifecycle management, with experience building trusted information programs at scale.
• Proven ability to lead cross-functional initiatives across engineering, security, AI, and business teams.
• Experience in FinTech, regulated industries, or AI-native companies, with enterprise knowledge platforms, AI readiness programs, and governance operating models spanning ownership, stewardship, and trust scoring is preferred.