Head of Data

Job description

**Vapi (/ˈVɑːpi/):** - Voice AI that resolves, not transfers - Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life - Trusted by 1 million developers building the future of voice agents - Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised - [Try talking to Vapi now!](https://vapi.ai/) ## **Why We’re Hiring This Role:** - Vapi has more data than clarity. One billion calls, millions of developer events, and an enterprise book growing 10x, but no single source of truth. - Finance, GTM, Product, and Engineering each have their own numbers. Alignment breaks down exactly when it matters most. - You will be our first Head of Data. You will build the function from scratch: the canonical metrics, the infrastructure behind them, and the culture that trusts them. - This is a leadership role reporting to the CFO. Every function's ability to move fast and move together depends on the work you do. ## **What You’ll Do:** - **Own the single source of truth.** Define and own Vapi's core metric set (ARR, NRR, churn, call volume, latency, reliability) and build the canonical data model every team pulls from. One definition of a billable call. One definition of an active customer. One number in the board deck. - **Make the GTM funnel measurable end to end.** From signup and first call, through activation, PQL, MQL, SQL, SQO, PoC, and closed won, to time-to-live, adoption health, expansion, and retention. Arbitrate conflicting definitions and drive adoption of shared logic. - **Run the operating cadence.** Own the data, dashboards, and narrative behind weekly and monthly business reviews, and instrument OKRs with reliable, current data. - **Build and scale the data platform.** Own the modern data stack end to end (warehouse, ingestion, transformation, orchestration, BI). Ship well-documented, tested dbt models and enforce data contracts between producers and consumers. - **Handle voice-API scale.** Design pipelines for call telemetry, transcript events, usage metering, billing signals, and model performance traces. Set freshness SLAs, alerting, and on-call coverage so data issues surface before they become decision errors. - **AI/LLM observability and monitoring.** Build pipelines for AI/LLM data pipeline monitoring, model telemetry, and prompt-to-performance observability. - **Unlock self-serve analytics.** Build canonical and semantic layers where Sales, Finance, CS, Product, and Engineering answer their own questions. Ship function-specific dashboards: GTM funnel and PoC win rate, revenue and cohorts, reliability and latency, activation and PQL rate. - **Own governance, quality, and access.** Build the definitions library, data dictionary, lineage, and access controls. Partner with Security and Legal on retention, residency, and PII and voice-data handling under HIPAA, GDPR, CCPA, and customer DPAs. - **Be a strategic partner.** Bring data into pricing, market expansion, product bets, and customer health. Partner with Finance on revenue recognition, usage-based billing, and investor reporting. Partner with GTM on pipeline health, territory design, and retention modeling. - **Build the team.** Own headcount planning, hire the first data engineers and analysts, and set the bar for high-craft, high-trust data work. Make build-versus-buy calls and own data vendor relationships. - **What Success Looks Like:** - **First 30 days:** Audit every source of truth today. Publish a metric definition v1 and a prioritized roadmap agreed with the CFO and leadership team. - **First 90 days:** One canonical model for ARR, NRR, and billable calls in production. Weekly business review runs on your data. - **First 6 months:** GTM funnel measurable end to end. Self-serve dashboards live for each function. First hires on the team. - **First year:** Leaders trust the numbers without asking where they came from. Data is a competitive advantage, not a shared frustration. ## **Who You Are:** - 10+ years in data, analytics, or data engineering, including building or leading a data function at a high-growth technology company. - You have shipped and sustained a company-wide single source of truth: aligned conflicting definitions, won over resistant stakeholders, and kept trust in the numbers over time. - Deep fluency in the modern data stack: dbt, Databricks, Fivetran or PostHog, and a BI layer like Hex. Strong SQL is a baseline; Python comfort is a plus. - Bias to action. You ship a working dashboard before you build the perfect one, then iterate. - You have built pipelines that handle billions of event-driven rows and know where the failure modes hide. - You partner equally well with Finance, Product, Engineering, and GTM. You earn trust by listening, scoping precisely, and delivering on time. - Sharp judgment on build-versus-buy, technical debt, and when good enough is right. You do not over-engineer for a company this size. - Clear, direct communicator. You can explain a metric discrepancy to a CFO and a pipeline architecture to a data engineer in the same day. - Experience with AI or ML data infrastructure: feature stores, model evaluation pipelines, or LLM observability. - **Bonus Points:** - First or founding data leader at a Series A through C company. - Background at a developer-facing platform, API business, or usage-based SaaS company. - Familiarity with usage-based billing data models and revenue metering systems. - Hands-on HIPAA or GDPR compliance in an analytics context. - Built data products for external customers, not just internal stakeholders. ## **How We Work:** - **Build something worthy of love** - Craft matters. We aim to build products and experiences customers genuinely love, not just tolerate. - **Commit and follow through** - We finish what we start and build trust by being people others can count on. - **Why not today?** - We value urgency and momentum. The fastest path to customer value usually wins. - **Seek raw input** - We go directly to customers, data, and teammates instead of relying on summaries or assumptions. - **It’s our problem** - We operate as one team. We share credit, own mistakes together, and support each other when things get hard. - **Be direct and kind** - We give feedback clearly, respectfully, and without delay. ## **Why Vapi:** - **Generational impact**: Build the *human interface* for every business - **Ownership culture**: Many of us are previous founders - **Kind team**: The founders, Jordan and Nikhil, are Canadians - **Tier-1 Investors**: YC, KP seed, Bessemer Series A ## **What We Offer:** - **Real stake**: We offer a competitive salary and excellent equity ownership - **Comprehensive health coverage**: medical, dental, and vision plans - **Team love**: We love hanging out, and we do quarterly off-sites - **Flexible time off**: take what you need - **More**: catered meals, transportation, gym, and a $10k annual L&D budget