Growth Engineer

Data quality is the bottleneck of the AI era. Every Fortune 500 is trying to solve it. We're the team they call.

Soda is the data quality layer for Disney, Ralph Lauren, CBRE, HelloFresh, 2K Games, and Nubank. The category is growing rapidly because AI doesn't work on bad data.

We're hiring a GTM Engineer to build the machinery that gets that message to the people who need it. You'll join the Growth team reporting to a co-founder, and build the systems the rest of the team runs on: content, visuals, videos, skills, agents- whatever the biggest constraint is that quarter. Your first and largest project is the content engine.

Requirements

We publish a lot - webinars, technical blogs, founder LinkedIn, product marketing - and most of it is still hand-made. Your job is to build a pipeline that turns a raw source into content a Staff Data Engineer or CDO with 20 years of experience would read and forward: real prompt engineering, a defined voice per author, evals that catch regressions, and the taste to kill output that's accurate and lifeless. Anti-slop is the point: an engine that ships slop faster has negative value. We build agentically here - Claude Code, MCP servers, and agent skills are the daily workflow.

What You'll Do

• Build the content engine end-to-end: ingestion, theme extraction, drafting, evals, and the review step 
• Create content including webinars and product videos
• Own and grow audience  
• Our team writes in distinct ways; the engine should sound like them, not like a model.
• Make quality measurable. 
• Own the numbers - reach, engagement, pipeline influence - and cut what doesn't work.
• Contribute the rest of the Growth stack as constraints move.
• Work directly with the founders, customers, customer engineers, to lean and improve on how Soda talks about the category. Your opinion matters here.

You Should Have

• 3+ years building things that go to market: growth engineering, marketing ops, technical content, RevOps, or a founder background. Titles vary; portfolios don't.
• You can write, story tell, and you can tell good writing from bad: send us something you wrote that a technical audience read. The most important line in this ad.
• Serious prompt engineering: multi-step LLM pipelines with structured outputs and evals, not chatting with a model. You know why the naive version produces slop.
• Enough code to be autonomous: Python or TypeScript, APIs, webhooks, a database. Nothing should be blocked waiting for an engineer.
• Generalist instinct: you find the constraint and fix it, and you'd rather build the workflow than do the task fifteen more times.
• Enough data fluency to be credible: you can hold your own on pipelines, dbt, and warehouses.
• Independence: you don't need hand-holding in a distributed, async team across 12+ countries.