Head of Data

Vapi•San Francisco, CA

6d•$200,000 - $240,000•Remote

About The Position

Vapi is seeking its first Head of Data to build the data function from scratch. The company has a significant amount of data from one billion calls, millions of developer events, and a rapidly growing enterprise customer base, but lacks a single source of truth. This leadership role, reporting to the CFO, will be responsible for establishing canonical metrics, the underlying infrastructure, and a data-driven culture. The Head of Data will play a critical role in enabling every function of the company to operate efficiently and cohesively.

Requirements

10+ years in data, analytics, or data engineering.
Experience building or leading a data function at a high-growth technology company.
Proven experience shipping and sustaining a company-wide single source of truth.
Deep fluency in the modern data stack: dbt, Databricks, Fivetran or PostHog, and a BI layer like Hex.
Strong SQL skills; Python comfort is a plus.
Bias to action: shipping working dashboards and iterating.
Experience building pipelines that handle billions of event-driven rows and understanding failure modes.
Ability to partner effectively with Finance, Product, Engineering, and GTM teams.
Sharp judgment on build-versus-buy, technical debt, and pragmatism.
Clear, direct communication skills.
Experience with AI or ML data infrastructure (feature stores, model evaluation pipelines, or LLM observability).

Nice To Haves

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.
Experience building data products for external customers.

Responsibilities

Define and own Vapi's core metric set (ARR, NRR, churn, call volume, latency, reliability) and build the canonical data model for all teams.
Make the GTM funnel measurable end to end, from signup to expansion and retention, arbitrating conflicting definitions and driving adoption of shared logic.
Own the data, dashboards, and narrative for weekly and monthly business reviews, and instrument OKRs with reliable data.
Build and scale the modern data stack, including warehouse, ingestion, transformation, orchestration, and BI.
Ship well-documented, tested dbt models and enforce data contracts.
Design pipelines for call telemetry, transcript events, usage metering, billing signals, and model performance traces at voice-API scale.
Set freshness SLAs, alerting, and on-call coverage for data pipelines.
Build pipelines for AI/LLM data pipeline monitoring, model telemetry, and prompt-to-performance observability.
Build canonical and semantic layers for self-serve analytics, enabling Sales, Finance, CS, Product, and Engineering to answer their own questions.
Ship function-specific dashboards for GTM funnel, revenue, reliability, and activation metrics.
Own data governance, quality, and access, including definitions library, data dictionary, lineage, and access controls.
Partner with Security and Legal on data retention, residency, PII, and voice-data handling under relevant regulations (HIPAA, GDPR, CCPA, DPAs).
Act as a strategic partner, bringing data insights to pricing, market expansion, product strategy, 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 data team by owning headcount planning, hiring data engineers and analysts, and setting standards for data work.
Make build-versus-buy decisions and manage data vendor relationships.