VP, Data

Role Overview

• 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.
• Revenue & Risk Intelligence
• Build data systems that accurately models 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 — and technical complexity into business understanding. Clearly articulate data definitions, tradeoffs, and system constraints. Serve as a trusted partner to Product, Engineering, Finance, and Executive Leadership in driving high-impact decisions.

Requirements

• 10+ years of experience in data engineering or data platform leadership, including prior VP / Head of Data Engineering scope (or equivalent)
• Proven ownership of data systems directly tied to revenue, billing, or financial outcomes
• Deep expertise in modern data architectures (batch + streaming, warehouses, orchestration, modeling)
• Comfortable doing vendor evaluations, build vs buy decisions, and success implementing infrastructure projects.
• Strong command of data quality, lineage, observability, and governance — with pragmatic execution
• Experience stewarding data lifecycle with ML models, both traditional supervised learning as well as LLM-based models
• Experience designing systems that accommodate ambiguity, delayed signals, and evolving business rules
• Ability to drive clarity and alignment where metrics are contested and incentives may compete
• Strong understanding of attribution, leading vs. lagging indicators, and decision-enabling data principles
• Clear judgment that timely, decision-enabling truth is more valuable than theoretical perfection
• Experience in affiliate marketing, marketplaces, fintech, adtech, or other revenue-complex environments strongly preferred.

Benefits

• Medical, Dental, and Vision Insurance
• Flexible PTO
• 13 paid company holidays annually
• Updater Stock Options
• 401(k) with employer match
• Wellbeing Subsidy
• One Medical membership
• Virtual on-demand healthcare through Teladoc and Talkspace
• Flexible spending account (FSA)
• Health savings account (HSA)
• Supplemental Short & Long Term Disability Insurance
• Supplemental Life Insurance
• Paid Parental Leave