Scribe Staff Analytics Engineer, GTM at Scribe responsible for building foundational GTM data models and enabling data-driven decision making. Partner with sales, marketing, finance, and RevOps to deliver trusted data products.
Responsibilities
As the Lead Analytics Engineer for GTM, you’ll be the first dedicated data hire for our go-to-market organization, reporting directly to the Head of Data. You’ll design and build the core data models that define how Scribe measures pipeline, bookings, revenue, and customer growth, and you’ll set the standards that future GTM analytics work is built on. As the team grows, you’ll have the opportunity to mentor and shape the analysts and analytics engineers who join it.
Working hand in hand with sales, marketing, finance, and RevOps, you will answer Scribe’s most critical go-to-market questions and turn them into durable, self-serve data products. Your work will be central to how we scale our enterprise motion, helping leadership understand what drives pipeline and revenue, and where to invest next.
Build Scribe’s foundational GTM data models from first principles, starting with Sales and extending across Marketing and Finance, so that metrics like pipeline, bookings, ARR, and conversion have one clear, consistent definition.
Turn ambiguous business questions into simple, actionable metrics, partnering directly with GTM and finance leaders to define the KPIs, dashboards, and analyses they run the business on.
Be a cross-functional magnet with our sales, marketing, and finance teams, establishing trusted partnerships and serving as the go-to resource for GTM data questions, deep-dive analysis, and technical guidance.
Lay the foundation of GTM data culture through reproducible work, documentation, data quality standards, and self-serve tooling that make data accessible to everyone in the GTM org.
Mentor and help grow the team as GTM analytics scales, setting the technical bar and best practices for the analysts and analytics engineers who follow.
What makes you a great fit
You’d be a great fit for this role if this sounds like you:
Have 8+ years of experience in analytics engineering, data engineering, or analytics, with significant time spent on Sales, Marketing, or Finance data at a SaaS company
Have built data models from the ground up, and know how to design for clarity, scale, and trust rather than inheriting what already exists
Strong technical proficiency in our tech stack – Snowflake, dbt cloud, Sigma, Mixpanel, and Looker – with expert SQL and data modeling skills
Qualification
Preferred
Experience working in high-paced Enterprise SaaS startups, especially during a shift from self-serve to enterprise sales
Experience mentoring analysts or analytics engineers, or serving as a tech lead on a data team
Experience creating a step-function change in a GTM team’s effectiveness with the help of AI tooling
