Head of Data & Analytics

** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** The Head of Data Analytics is a high-visibility, foundational role responsible for establishing the company's single source of truth for data across all functions. Acting as the analytical backbone of the business, you will ensure every critical metric is defined, governed, and reportable from one place — giving leadership the data clarity they need to make fast, confident decisions. You will translate raw data across a modern SaaS stack into a trustworthy, scalable intelligence layer that the entire organization can rely on. This role is designed for a seasoned data leader who excels at building from scratch — someone who can architect a data platform, establish governance standards, and be a genuine strategic partner to senior leaders – not just delivering data, but shaping decisions. You will connect data to business context, identify what matters, and provide clear, prescriptive recommendations. Reporting directly to the SVP of Business Operations, you will own the data infrastructure that underpins our next phase of growth. This role is intentionally hands-on to start. You will personally build and shape the foundation of our data platform while partnering closely with leaders across the business. As we scale, you will have the opportunity to evolve into a player-coach, building and leading a small but high-impact data team. In the first 6-12 months, you will: Establish a clear, trusted definition of core company metrics across GTM, Product, Finance, and Customer Success Reduce reliance on manual reporting by automating high-impact workflows Build a scalable data model that connects our core systems into a coherent source of truth Enable leadership to access and trust data without needing constant ad hoc support What you can expect as the Head of Data Analytics: Build the single source of truth: Audit, rationalize, and own the company's data model end to end — from raw sources through transformation to consumption. Every key metric will have one definition, one owner, and one place to find it. Identify the highest-impact manual reporting workflows across functions and automate them : Today, much of our reporting lives across spreadsheets and manual workflows, with no single owner of data. One of your first priorities will be to bring structure, consistency, and trust to this environment, and build a self-serve analytics layer that increases data trust and reduces ad hoc requests across the company. Own executive and board-level reporting: Build and maintain the metrics layer that leadership, the board, and ultimately investors rely on — each defined, documented, and reportable from a single governed layer. Mature the dbt layer: Partner with engineering team to audit existing dbt models, close gaps, and establish transformation standards that will scale the platform. You won't be coding alone, but you need to be fluent enough to review, direct, and govern the work. Establish metric governance: Define the operating model for how metrics are created, changed, and communicated — including a cross-functional process for resolving metric disputes and maintaining a company-wide data dictionary that becomes the authoritative reference. Build a scalable, auditable data foundation: Ensure our data is structured, documented, and fully traceable from source systems to reported metrics. Establish clear data lineage, metric definitions, and governance so leadership can rely on data with confidence as reporting needs become more complex. Act as a strategic partner to senior leadership: Show up to QBRs, pipeline reviews, and planning cycles with a clear point of view on what the data means and what the business should do next. Be the person who changes decisions — not by reporting the data, but by interpreting it and making actionable recommendations. Cross-functional data leadership: P ... (truncated, view full listing at source)