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Salary: USD 120,000 - 130,000 / annual
Soda is a data quality platform serving Fortune 500 companies including Disney, Ralph Lauren, CBRE, HelloFresh, 2K Games, and Nubank. The company is hiring a Growth Engineer to build the systems and infrastructure that power the go-to-market motion.
You'll report directly to a co-founder and own the content engine—a critical project to automate and scale content production across webinars, technical blogs, founder LinkedIn, and product marketing. Currently most content is hand-made; your role is to build an end-to-end pipeline that transforms raw sources into high-quality, publication-ready content that resonates with technical audiences (Staff Data Engineers, CDOs, etc.).
Key responsibilities include:
- Design and build the content engine: ingestion, theme extraction, drafting, evaluation, and review workflows
- Implement serious prompt engineering: multi-step LLM pipelines with structured outputs and quality evals to eliminate low-quality output
- Own content creation including webinars and product videos
- Build and grow audience reach; measure and optimize engagement and pipeline influence
- Ensure the engine captures distinct author voices rather than generic model output
- Contribute to broader growth stack as priorities shift
- Work directly with founders and customers to refine how Soda communicates its category
You should have 3+ years building go-to-market systems (growth engineering, marketing ops, technical content, RevOps, or founder experience). Strong writing and storytelling skills are essential—you can distinguish excellent technical writing from mediocre. You need hands-on prompt engineering expertise, Python or TypeScript proficiency, and familiarity with APIs, webhooks, and databases. Data fluency (pipelines, dbt, warehouses) and independence in async, distributed teams are important. Fluent English required.
Bonus experience includes marketing/growth in data, developer tools, or infrastructure; growing your own technical audience; building agentic workflows; or data quality/observability domain knowledge.
The company values freedom with responsibility, transparency, and direct communication. You'll have full autonomy, work flexible hours across 12+ countries, and have access to all frontier AI models. The role is fast-paced with rapidly evolving priorities and no existing playbook—you'll be judged on output and impact, not process.
