> Markdown version of [/jobs/ext/2547570-gtm-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/2547570-gtm-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GTM Analytics Engineer - **Company:** DECAGON, LLC - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $190,000.0 - $230,000.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Big Data, BigQuery, Software as a Service, Data Infrastructure, Extract Transform Load (ETL), Data Structures, Data Warehousing, Database Queries, Salesforce.Com, Build Management, Data Lakes, Data Pipelines - **Published:** August 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2568c701da0eefe4 ## About the Role * 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 ## Description 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.", * 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 ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) ## Related Articles - [How to Turn Community Events Into a Powerful AI GTM Engine: The Daytona Playbook](https://www.wearedevelopers.com/magazine/732-how-to-turn-community-events-into-a-powerful-ai-gtm-engine-the-daytona-playbook) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again)