Head of Business Data

The world’s most influential enterprises trust Zip, including T-Mobile, OpenAI, AMD, Mars, Dollar Tree, and more. Together they’ve saved over $8 billion and processed over $500 billion in spend. Zip’s team includes product leaders from Apple, Airbnb, and Meta, as well as former procurement leaders from United Health...

Backed by Adams Street, Alkeon, BOND, CRV, DST, Tiger Global, and Y Combinator, Zip has raised $371 million, most recently at a $2.2 billion valuation and has been recognized by Forbes Fintech 50, Fast Company's Most Innovative Companies, Inc. Best in Business, and LinkedIn Top Startups.

We are a rapidly scaling, late-stage SaaS company experiencing hyper-growth. As we enter our next phase of maturity, data is at the center of our strategy - powering everything from executive decision-making to an AI-first GTM engagement model.

We are looking for a strategic, highly commercial, and visionary Head of Business Data to lead our Business Intelligence and GTM Data Science functions. In this role, you will define the business data layer, acting as the bridge between our Go-To-Market (GTM) engines, finance, and our core Product Data Engineering team. You will ensure we have a flawless "single source of truth" across the enterprise, build out our comprehensive dashboarding ecosystem, and lay the strategic data foundation necessary to power our upcoming AI initiatives.
Set the Zip Data Strategy: Act as the primary visionary for how we leverage internal business data. You will define the overarching data strategy for Zip, mapping out how our internal data ecosystem needs to evolve to support hyper-growth, new product lines, and global scale.
Lead Business Intelligence & GTM Analytics: Own the end-to-end dashboarding and reporting ecosystem. You will build and maintain the core Executive Dashboard, targeted dashboards for GTM leadership, and operational views for customer-facing teams.
Pioneer AI Data Foundations: Architect the data strategy required to unlock AI capabilities. You will structure and expose usage and business data so we can programmatically build automated, intelligent outputs - such as dynamically generated, data-backed presentation decks for our clients.
Own the Business "Single Source of Truth": Partner closely with Finance, Revenue Operations, and Product to define, standardize, and track critical SaaS metrics (e.g., ARR, NDR, Gross Retention, CAC, LTV, Magic Number) via a robust semantic layer.
Partner with Core Data Engineering: Collaborate deeply with the Product Data Engineering team (who owns core product tables and overarching infrastructure) to ensure the business data layer is seamlessly integrated, performant, and reliable.
Build & Scale the Team: Hire, mentor, and lead a high-performing organization of analytics engineers, BI developers, and data analysts.
Drive Executive & Board Reporting: Deliver pristine, automated financial and operational reporting utilized by the executive team, Board of Directors, and external stakeholders.

10+ years of progressive experience in data analytics, business intelligence, or analytics engineering, with at least 5+ years in a senior leadership role managing managers.
Proven SaaS DNA: Deep understanding of B2B SaaS business models, unit economics, and standard metrics. You have successfully navigated the complexities of enterprise SaaS billing, CRM data (Salesforce), and financial data.
Cross-Functional Influence: Proven ability to partner effectively with highly technical engineering teams while delivering clear, commercial value to GTM and Finance leaders.
Executive Presence: Exceptional ability to translate complex data concepts into clear business narratives for C-level executives and investors.
Deep expertise in the Modern Data Stack, specifically focused on the analytics and BI layers (e.g., dbt, Looker, Tableau, Sigma).
Strong foundations in data modeling, dimensional modeling, and establishing a governed semantic layer.
Strategic understanding of how to structure, model, and serve data to power Large Language Models (LLMs) and embedded AI features.
Deep understanding of the intersection between GTM systems (Salesforce, Marketo, CS platforms) and back-office financial systems (NetSuite, Stripe, etc.).
Experience preparing a company's data infrastructure for public market readiness (IPO) or leading data diligence during late-stage fundraises.