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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GTM Data Analyst - **Company:** n8n - **Location:** Netherlands - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, BigQuery, Python (Programming Language), Open Source Technology, Salesforce.Com, SQL Databases, Pandas, Scikit Learn, Statistics Packages - **Published:** September 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=1a9f7f8d613bafc4 ## About the Role * Senior GTM analytics chops: 5+ years in sales, revenue or GTM analytics at B2B SaaS, with real ownership of the sales funnel. * Sales metrics fluency: pipeline coverage, stage conversion, velocity, win rate, ACV, quota attainment, ramp, ARR/NRR - you think in these natively. * CRM depth: experience with Salesforce (or equivalent) - its structure, its quirks, and the hygiene problems that quietly ruin analyses. * Forecasting experience: you've built or contributed to forecast models and know what makes them defensible - here you'll support RevOps on the build. * Technical toolkit: expert SQL; comfortable in a modern warehouse stack (BigQuery, dbt, Metabase/Hex or equivalent). * Planning experience: territory, quota or capacity modelling for a real sales org. * Business partner mindset: credible with sales leaders and reps, and able to tell a VP they're reading the data wrong. * Opinionated and high-agency: you spot what's worth analysing, you do it, and you arrive with a recommendation. * Communication that lands: memos and readouts that change what people do next. Nice-to-haves * PLG experience, especially the self-serve to sales-assisted handoff. * Usage-based or credit-based pricing: you've analysed consumption revenue before. * Scoring and propensity models: lead or account scoring, statistical or ML-based. * Python for analysis: pandas, statsmodels, scikit-learn when SQL isn't enough. * Devtool, open-source or technical product experience. * Wider GTM stack: Gong, Clay, enrichment and intent data, marketing attribution. * dbt modelling: you can ship your own models rather than only file requests. ## Description Our commercial motion has two engines running at once: a self-serve product that thousands of developers adopt on their own, and an enterprise sales team closing the accounts that grow out of it. We've moved to usage-based pricing, migrated to Salesforce, and built a serious data foundation. What we don't have yet is someone whose entire job is making sense of the sales side of it. That's this role. You'll own the analytics behind pipeline, funnel conversion and GTM planning, and partner with RevOps on the forecast - sitting inside the data team, embedded with RevOps and Sales, and in the room when the plan gets made. Your mission: make our sales org measurably better at forecasting, prioritising and converting Own pipeline analytics, support forecasting * Build the models and views that tell us where pipeline actually stands - coverage, stage conversion, velocity, slippage. * Support RevOps on forecasting: supply the analysis and accuracy tracking behind it, and be the person leadership trusts to explain the number when it's uncomfortable. * Run win/loss analysis that goes past "price" and "timing" to something we can act on. Connect product-led growth to sales * We have thousands of self-serve users and a sales team that can only talk to a fraction of them. Your job is to work out which fraction. * Build account and lead scoring on product usage and firmographic signal, with RevOps and the product/customer analysts. * Sharpen PQL and MQL definitions until reps trust what lands in their queue. Shape how we plan * Model territories, quota and capacity for annual planning - and make the trade-offs visible. * Segment the base: which accounts, which motions, which segments actually pay back the effort. * Answer the questions that decide where the next euro of GTM spend goes. Build foundations people trust * Partner with Analytics Engineering on Salesforce and product data models in dbt/BigQuery. * Standardise metric definitions so "win rate" means one thing across sales, marketing and finance. * Ship dashboards GTM managers genuinely run their week on - not decks that get opened once. Bring a point of view * Sit in pipeline reviews and planning as a peer, not a reporting function. * Push back constructively, including on the numbers people are attached to. * Turn analysis into crisp, written recommendations that move decisions., You'd be the first person here whose whole job is the sales data - which means you get to define the function rather than inherit someone else's version of it. The commercial problem is interesting: a product-led motion and an enterprise motion feeding each other, on usage-based pricing, in a category that's moving very fast. The foundations are already there. A real data team maintains the stack (BigQuery, dbt, Dagster, Metabase, Salesforce), so you spend your time on analysis rather than firefighting pipelines. And you'll work directly with GTM leadership in a company that values autonomy, directness and impact over process. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Building Talent Acquisitions Teams](https://www.wearedevelopers.com/videos/1496-building-talent-acquisitions-teams) - [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [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) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Analyst Salary Germany](https://www.wearedevelopers.com/magazine/277-data-analyst-salary-germany)