Lead our enterprise data organization through its next stage of modernization and integration
Unify Data Engineering, Data Science, Revenue Analytics, and Business Intelligence into a cohesive, high-performing organization
Drive architectural stabilization, governance clarity, and improved decision velocity across the company
Establish a trusted single source of truth for core enterprise metrics
Define and execute a multi-year enterprise data roadmap spanning engineering, analytics, and science
Own the identification and mitigation of enterprise data risks
Execute a multi-year modernization plan to democratize data consumption across the company
Drive the evolution from static reporting to near real-time, decision-ready intelligence across marketplace performance, revenue operations, and executive KPIs
Integrate and align multidisciplinary data functions under a unified operating model

15+ years of progressive data leadership experience, with 5+ years at the VP/SVP level leading multidisciplinary organizations across data engineering, analytics, and data science
Demonstrated history influencing C-suite leaders and public company Boards to secure investment and deliver enterprise-scale data transformation initiatives
Strong foundational experience in database architecture, data engineering, or data platform design, with the ability to deeply understand data pipelines, schema design, and system-level data integrity
Demonstrated ability to steer and evaluate enterprise data platform decisions across storage, compute, orchestration, and semantic modeling, prioritizing long-term architectural integrity over tool familiarity
Proven track record guiding teams toward trusted, high-integrity data pipelines and "single source of truth" environments
Experience selecting and evolving data stack components based on business needs and scalability requirements
Working understanding of the systems, data infrastructure, and experimentation frameworks required to enable scalable AI/ML initiatives
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline, or equivalent practical experience.
Advanced degree (e.g., MS, MBA) is a plus but not required.

VP, Head of Data

Key skills