Founding Data Engineer

Description:

You'll own data infrastructure end-to-end - ingestion, transformation, storage, delivery.

The current agent system works. Your job is to scale it: more documents, more asset classes, more clients. You'll make architecture decisions, push the boundaries of agentic tooling and ship data as a product to institutional buyers who rely on it for decisions that move millions.

Full ownership from day one, with a genuine progression trajectory for the right person.

This is a predominantly backend/infra DE role. No dashboards, no stakeholder reporting - just the engine that powers everything. You'll be the most senior person in your domain from day one, with no one above you in this function - and a clear path to leadership later down the line.

✅ Must have requirements:

• Roughly 3-6 years experience building performant data pipelines and ML systems in production at a company where data is the core product, not a support function
• Genuinely AI-native experience: Claude Code, Cursor or equivalent as your daily environment - not occasional experiments
• Python, Postgres, async, queues - fluent and battle-tested
• Experience in a small team (2-30 people) where you owned the whole function without a safety net
• Data quality obsessive - inconsistencies bother you until they're fixed, not flagged and forgotten

👍 Bonus points for:

• Experience at a financial data provider (Bloomberg, Refinitiv, Preqin, FactSet etc.) or quant finance
• Experience with LLMs in production / agentic workflow design
• Web scraping and document parsing at scale
• Staff/Principal-level IC ownership at a larger org