GTM Engineer

Overview In this role you will shape the revenue technology that powers Nominal’s GTM operations. You’ll integrate data across Salesforce, Gong, Slack, and enrichment sources, building pipelines and internal tools that convert data into action. You’ll partner with Sales, Marketing, CS, and Data to improve forecast, scoring, and deal workflows. This is a hands-on, cross-functional position at the intersection of hardware and software, focused on speed, safety, and scalable growth. You’ll own and evolve the GTM tooling stack to support a fast-moving revenue engine. Compensation / Benefits100% coverage of medical, dental, and visionUnlimited PTO and sick leaveFree lunch, snacks, and coffeeProfessional development stipendAnnual company retreat ResponsibilitiesLearn and extend the Salesforce and sales tooling architecture; understand data model, field taxonomy, and dependency logicBuild data pipelines moving information between Salesforce, Gong, Common Room, Slack, and enrichment sources; ensure accuracy and live stateShip internal tools (forecast trackers, scoring dashboards, comp calculators, deal-desk monitoring) per specsDevelop signal-based and AI-driven workflows for routing, enrichment, next-best-action, and outreach across the funnelSupport Area Directors, AEs, and CS with tools; surface friction and prioritize fixes with manager guidanceDefine and defend data quality across the stack (pipeline health, field hygiene, sync integrity)Own and maintain code repositories for internal GTM tooling to ensure maintainability, security, and compliancePrototype and iterate on new tooling and integrations as the GTM function evolves Key requirements2+ years in analytical, data engineering, or software engineering roleSQL and at least one scripting language (Python preferred) with scope-driven developmentFluent with AI tooling and applying it to enrichment, scoring, drafting, or agentic workflowsExperience building end-to-end data pipelines and understanding inputs, transformations, and outputsAbility to take a clearly scoped problem and deliver a working tool; asks clarifying questions when neededAbility to quantify impact in revenue terms (pipeline influenced, hours saved, cost per lead)Commitment to data governance, quality, and integrity in fast-moving software systemsAbility to design software interfaces that scale with a revenue organizationproblem solvingclarity in communicationcollaboration across multiple teamsSQLPythondata pipelines