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