Director of Revenue Intelligence

OpenLoop Health

About The Position

Great revenue teams don't just generate data—they act on it. At OpenLoop, we're building the analytical infrastructure that turns raw pipeline and customer data into the insights that drive confident decisions. We're looking for a Director of Revenue Intelligence to own that infrastructure: from how data flows across our GTM systems to the reporting and analytics that serve every corner of our revenue organization. This role sits at the intersection of revenue operations and strategic analytics. You're not just building reports—you're building the single source of truth that leadership, sales, marketing, and CS rely on every day. And you're designing the systems foundation that will support AI-assisted forecasting and planning as the business scales. You'll partner directly with GTM leaders, Finance, and the broader RevOps team, and you'll build a team of revenue analysts as the function grows. If you're energized by making revenue data reliable, accessible, and actionable—and frustrated when teams are working from different numbers—this role was written for you. Fragmented data and inconsistent reporting are limiting OpenLoop's ability to forecast with confidence, understand customer health, and make fast, high-quality decisions. Data lives across Salesforce, HubSpot, financial systems, and product analytics—without a unified, governed layer connecting them. This role creates that layer. You'll establish a reliable, scalable reporting foundation that makes every revenue metric trustworthy—and makes it possible to build AI-powered analytics and forecasting on top of clean, well-structured data.

Requirements

8+ years of experience in revenue operations or revenue analytics at a B2B SaaS company
Expert-level proficiency in Salesforce and/or HubSpot, including data modeling, object architecture, and CRM governance
Strong command of SQL and experience working with BI platforms such as Looker, Tableau, or similar
Deep fluency in SaaS revenue metrics: ARR, pipeline coverage, churn, NRR, CAC, LTV
Proven ability to build and maintain revenue reporting systems that scale across GTM functions
Experience partnering with Finance on forecasting models and revenue planning
Ability to work cross-functionally and translate business questions into data solutions
Comfortable being both a hands-on builder and a strategic thought partner
Experience at a growth-stage startup; comfortable with ambiguity and rapid iteration

Nice To Haves

Exposure to AI-assisted forecasting or revenue intelligence platforms (e.g., Clari, Gong, People.ai) a strong plus

Responsibilities

Revenue Systems Governance – Own the data integrity and architecture of OpenLoop's core revenue systems—Salesforce, HubSpot, and connected financial platforms—ensuring that what lives in the CRM is clean, complete, and consistent across the revenue org.
Data Modeling & Metric Definitions – Define and maintain canonical revenue data models covering pipeline, ARR, retention, expansion, and customer health—so every team is working from the same definitions and the same numbers.
Reporting & Self-Serve Analytics – Design and own dashboards and self-serve analytics in Looker or equivalent BI tools—giving GTM leaders and ICs visibility into the metrics that matter without waiting on the data team.
Forecasting Infrastructure – Partner with RevOps and Finance to build and maintain the reporting infrastructure that underpins revenue forecasting—ensuring pipeline data is clean, stage definitions are consistent, and forecast inputs are reliable.
Data Quality & Governance – Own data quality across the revenue tech stack—establishing validation frameworks, auditing CRM hygiene, resolving issues proactively, and maintaining the trust that makes self-serve analytics possible.
Revenue Tech Stack Optimization – Evaluate, configure, and evolve the tools that power revenue intelligence—from CRM configuration to BI tooling—ensuring the stack serves the business's analytical needs today and tomorrow.
AI/ML Enablement – Structure and expose data assets in ways that support future AI and ML use cases—so when the business is ready to build, the data foundation is already there.
Cross-Functional Partnership – Work closely with Sales, Marketing, Finance, and CS to define KPIs, reporting requirements, and analytical priorities—translating business questions into data solutions.
Team Leadership – Hire and develop a team of revenue analysts over time, building a function that scales with the business.