Head of Data- Business & GTM

Head of Data- Business & GTM

We are an AI platform Tech Startup for the enterprise. We are disrupting & transforming a $38B industry. We are in hyper-growth looking for Head of Data to own our Business GTM & Enterprise sales Data Strategy. We have global vision for our AI-product and we are expanding to support our growth. (We have grown 3X!) to innovate faster than ever before.
Backed by top investors and Y Combinator we have raised over $275 million most recently at a $2.1 billion valuation. We were voted one of the most Innovative Companies to work for and Top Startups.

Your Role
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 and visionary Head of Business Data to lead our Business Intelligence and GTM Data Science 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.
Responsibilities

• Set the Data Strategy: Act as the primary visionary for how we leverage internal business data. You will define the overarching data strategy 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. : Deliver pristine automated financial and operational reporting utilized by the executive team Board of Directors and external stakeholders.

Qualifications
Experience & Leadership

• 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.

Technical Expertise

• Deep expertise in the Modern Data Stack specifically focused on the analytics and BI layers (e.g. dbt Looker Tableau Sigma). And strong hands-on knowledge of Python SQL modern ETL tools cloud data warehouses(e.g. PyTorch TensorFlow scikit-learn) a plus.
• 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 companys data infrastructure for public market readiness (IPO) or leading data diligence during late-stage fundraises is a plus.
• Bachelors Degree or Masters in Data Science Computer Science Statistics or related quantitative field.