GTM Analytics Engineer

Decagon is looking for its first GTM Analytics Engineer to build the data infrastructure that our entire go-to-market organization runs on. You'll own turning that raw, messy data into clean, well-modeled tables that the rest of RevOps, sales leadership, and the exec team can actually build on. This is a true 0-to-1 role with support from the broader RevOps & GTM team: you'll design lots of data structures and modeling layers from the ground up, set the standards for how GTM data gets structured, and become the trusted person to answer "where does this number actually come from."

In this role, you will

Design and build the foundational GTM data infrastructure in BigQuery — ingesting, organizing, and modeling data from Salesforce, Gong, Outreach, and other GTM systems into a reliable data lake

Write and maintain models that transform raw CRM and GTM tool data into clean, trusted tables for pipeline, forecasting, segmentation, comp, and territory reporting

Partner with sales leadership and cross-functional partners to translate ambiguous, ad hoc reporting requests into durable, well-documented data models rather than one-off queries

Build and maintain data pipelines that keep GTM data fresh, accurate, and consistent as new tools and data sources get added

Own data quality end-to-end — establishing testing, validation, and monitoring so the numbers in Hex are numbers people trust

Set technical standards and best practices for GTM data modeling as the function scales

Your background looks something like this

4+ years of experience in data/analytics engineering, with hands-on ownership of ETL/ELT pipelines and dbt in a production environment

Strong SQL skills and direct experience building and maintaining data warehouses in BigQuery (or a comparable cloud warehouse)

Real experience working with GTM data — Salesforce is a must, plus familiarity with tools like Gong, Outreach, or similar sales engagement platforms in a high-growth B2B company is a plus

Strong grasp of core SaaS and GTM metrics — conversion rates, ARR/NRR, win rates, sales cycle length, quota attainment — and how they're derived from the underlying GTM tool data

Comfort turning messy, inconsistent source data into clean, well-organized, documented tables built for downstream reporting and dashboarding

Experience creating outputs, including dashboards, ad hoc analysis with large datasets in BI tools (Hex preferred) for dashboarding and self-serve analytics

A builder mindset — you're excited to build foundational infrastructure from scratch in a fast-moving environment rather than maintain an existing system

Strong cross-functional communication skills; you can work directly with sales leadership to understand what they actually need, not just what they ask for