VP, Data
View All Jobs
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 / He