Head of Data & Analytics

LaunchDarkly•Oakland, CA

6h•Remote

About The Position

LaunchDarkly is creating a dedicated Head of Data & Analytics role to establish a single, accountable owner for the company’s most critical data, metrics, and analytical foundations. This role exists to ensure LaunchDarkly operates with watertight, auditable, executive-grade metrics as the business scales and prepares for the future. Reporting to the CFO, the Head of Data & Analytics will define, govern, automate, and certify the metrics that matter most to LaunchDarkly (e.g., ARR, NRR, GRR, Customer Count, product-level ARR), while partnering closely with Finance, GTM, Product, and Engineering. While multiple teams contribute data and analysis today, this leader will work collaboratively with all teams to ensure the metrics that matter most are always available, represented in useful & insightful ways and are 100% accurate and consistent Preference is for this person to be based in the Bay Area, but are open to considering remote US. The Head of Data & Analytics will: Create one authoritative source of truth for company-critical metrics Eliminate loose definitions, inconsistent nomenclature, and manual reconciliation Deliver real-time, executive-ready dashboards with full auditability Establish governance and self-validation processes so metrics remain correct over time Build predictive capability for the metrics that drive company value

Requirements

SaaS & Scale Experience Proven experience owning company-level metrics in a B2B SaaS company at ~$200M+ ARR Direct exposure to Board reporting, or pre-IPO data readiness Deep understanding of SaaS metrics and their edge cases 10+ years of progressive analytics and data leadership experience, including ownership of company-level metrics.
Data & Analytics Leadership Experience defining metric taxonomies and governance models across complex organizations Ability to work effectively in matrixed environments with Finance, GTM, Product, and Engineering Track record of eliminating data ambiguity and rebuilding trust in numbers
Technical & Analytical Depth Strong understanding of modern data architectures, BI tools, and analytics workflows Comfort partnering with Data Engineering teams that own pipelines and platforms Ability to go deep when needed, but operate primarily at the executive and systems level
Executive Presence & Judgment Clear, confident communicator who can challenge assumptions respectfully Trusted partner to CFO, CEO, and executive leadership High integrity and appreciation for the accountability and liability associated with company-critical data

Responsibilities

Company-Critical Metrics Ownership Define precise, unambiguous definitions for LaunchDarkly’s core metrics (ARR, NRR, GRR, FCF, product-level ARR, etc.), including all edge cases and use cases Own the final certification of these metrics across all internal and external reporting Ensure metrics are consistent across Finance, GTM, Product, and Executive reporting
Reporting, Dashboards & Automation Working with other company analytics teams, build and maintain real-time executive dashboards for core metrics and leading indicators Ensure all recurring reporting is fully automated once stabilized Eliminate manual, spreadsheet-driven, or analyst-dependent reporting processes
Governance, Quality & “Watertight” Data Establish data governance processes so metric changes follow defined approval and change-management workflows Implement validation, reconciliation, and self-audit mechanisms to ensure ongoing accuracy Act as the executive owner for data trust, accuracy, and reliability
Predictive & Forward-Looking Analytics Develop predictive views for key metrics such as ARR growth, NRR, churn, and free cash flow Partner with FP&A to ensure forecasts and long-range plans are grounded in trusted data Identify leading indicators and early warning signals for performance risks and opportunities
Cross-Functional Leadership (Without Direct Control) Coordinate a working group across GTM Analytics, Data Engineering, Product Analytics, and Finance Partner closely with Engineering (who retains ownership of data infrastructure and pipelines) and GTM teams (who may produce functional analytics) Drive alignment and outcomes through influence, clarity, and credibility rather than hierarchy
Team & Operating Model Directly manage a small, high-leverage analytics team (initially 1–2 analysts, potentially in lower-cost regions) Design a scalable operating model that balances centralized metric ownership with distributed analytics execution Maintain high velocity while operating with CFO-level rigor and discipline