VP, Data

What Success Looks Like

• Stakeholders trust the numbers—even when they’re uncomfortable
• Revenue questions that once took weeks now take hours or minutes
• Leading indicators surface risk before it hits the P&L
• KPIs are clearly defined, role-aware, and consistently interpreted
• Data enables faster, smarter decision-making across the company
• External data anomalies get identified immediately, rather than weeks later
• Clearly defined schema, data usage rules, and organizational understanding both in a financial and product landscape.
• Data can be consumed by humans and AI models with the correct semantic boundaries.

Key Responsibilities

• Data Strategy & Architecture - Own the long-term data strategy in partnership with Engineering, Finance, Product, and Executive Leadership. Define and evolve the end-to-end data architecture across acquisition, transactions, fulfillment, revenue recognition, and lifecycle events. Design scalable, auditable systems that accurately model complex, multi-role KPIs while balancing speed, accuracy, and cost. Current stack includes Snowflake, Looker, Python, Postgres, and SQL Server.
• Revenue & Risk Intelligence - Build data systems that accurately model affiliate revenue-share agreements, confirmations, cancellations, and adjustments. Enable early detection of fraud and performance anomalies before they materially impact margin. Partner with Finance and cross-functional leaders to establish canonical revenue metrics and shared KPI definitions.
• Time-to-Insight - Reduce the latency between business events and actionable insight. Enable faster experimentation, channel optimization, and partner performance analysis through reliable pipelines and tooling that support both real-time visibility and deep historical analysis.
• Leadership & Team Management - Build and scale a high-performing data engineering organization grounded in technical excellence, data quality, and operational rigor. Foster a collaborative, high-ownership culture that empowers teams to do their best work, operate effectively in ambiguity, and deliver durable systems that accelerate business impact.
• Cross-Functional Influence - Translate business ambiguity into technical clarity