GTM Engineer, Nominal

• You have 2–4 years of experience in data engineering, software engineering, analytics engineering, technical revops, or another highly technical role where you built production systems
• You have strong software engineering fundamentals and can understand, modify, and own the systems you build rather than relying on AI-generated code you can't explain
• You are comfortable working with SQL and Python and have experience interacting with databases, APIs, and data pipelines
• You've built systems that move and transform data across multiple sources and can explain the architecture, tradeoffs, and reliability considerations behind them
• You're highly fluent with modern AI development tools and actively use them to build faster, explore unfamiliar systems, and automate work
• You have unusually high agency. When you encounter something you don't know, your instinct is to learn it, build it, and figure out how to make it work
• You communicate clearly with both technical and non-technical partners and can translate an ambiguous business problem into a technical system
• You're excited by the idea of applying engineering to revenue problems rather than needing everything you build to live inside the core product

Desirable

• Nominal's revenue organization generates an enormous amount of data across our customers, products, and market. Today, turning that data into action still requires too much manual work and too many disconnected systems
• We're hiring our first GTM Engineer to change that. You'll build the technical infrastructure that helps Nominal identify the right customers, understand when they're ready for us, and turn signals across our market and product into action. That means building data pipelines, internal tools, AI-powered workflows, and systems that connect our GTM stack
• This is an engineering role embedded within Revenue Operations. You'll own problems from idea to production, work directly with GTM leaders and engineers, and have significant freedom in how you solve them
• Build our GTM data infrastructure. Connect data across Salesforce, Snowflake, Gong, enrichment sources, and external APIs into reliable pipelines and models that the revenue organization can act on
• Create a signal engine for our market. Develop systems that identify external signals indicating when companies are likely to need Nominal, ingest and structure that information, and turn it into dynamic account scoring and prioritization
• Build internal products from the ground up. Own tools for territory planning, account intelligence, forecasting, reporting, and other workflows from initial problem through deployment and iteration
• Use AI as a core development tool and product primitive. Build agents and automated workflows that transform unstructured information, surface insights, enrich data, and eliminate manual work across the GTM organization
• Turn product usage into revenue signal. Build pipelines and workflows that identify meaningful changes in customer behavior and make that information actionable for the teams supporting those customers
• Own what you ship. Maintain the repositories, pipelines, integrations, monitoring, and data quality behind your systems and ensure they remain reliable as Nominal scales
• Find problems worth solving. Work directly with Sales, Marketing, Customer Success, and Revenue Operations to understand how work happens today, identify opportunities for leverage, and determine what should be automated or rebuilt