VP, Data

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Updater operates at the intersection of affiliate marketing, embedded commerce, and consumer marketplaces where we create (and lose) revenue through complex, multi-party data flows. In this environment, data isn’t a support function—data runs the business.

We’re seeking a VP of Data to materially elevate how we make data-driven decisions across the company. Reporting to the SVP of Engineering, this leader will architect the systems, standards, and team that transform fragmented signals into trusted, decision-enabling intelligence.

This business-critical leadership role will directly impact growth, margin, risk mitigation, and executive velocity. You will build the canonical data engine powering a complex B2B2C marketplace—increasing trust, speed, and profitability through better systems and sharper insight.

We’re also aggressively leaning into machine learning and AI. We’ve been developing LLM-based agentic models to help consumers purchase complex products with confidence. In addition the engineering and data teams have been utilizing Claude Code, Codex, and other LLM-based tools to increase insights and productivity. We believe strongly in being a thought leader in this space. 

If you’re motivated by meaningful ownership and the chance to turn complexity into competitive advantage, this role offers a rare opportunity to do exactly that.

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 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

Compensation

This posting is anticipated to remain open until 5/8/2026. The new hire salary range for this position is $275,000 - $310,000 annually. Factors which may affect the starting pay within this range include skills, experience, and other qualifications aligned with Updater's internal leveling guidelines.