Data Engineer | Health Tech | Central London
They're using AI to automatically extract, categorise, and reconcile data from these scattered sources, turning chaos into actionable insights in the healthcare sector.
What You'll Be Doing
Working directly with the CTO, you'll own large parts of the data infrastructure:
What They Need
The Stack
Data: Dagster, Airbyte (custom connectors), dbt, BigQuery, Cube, Metabase, PostgreSQL/Supabase AI: LLMs via Google Vertex & Azure AI Foundry for document extraction Rest of stack: TypeScript, Next.js, Node.js
Bonus Points
Why This One's Different
If you want to building something that actually matters—and want proper ownership in an early-stage environment—this is worth a look.
They're using AI to automatically extract, categorise, and reconcile data from these scattered sources, turning chaos into actionable insights in the healthcare sector.
What You'll Be Doing
Working directly with the CTO, you'll own large parts of the data infrastructure:
- Building scalable data ingestion and processing systems for complex integrations.
- Taking problems from concept to production—making smart decisions.
- Designing ELT pipelines, working with unstructured data, and transforming raw data into customer-facing analytics
- Some data transformation and analysis work (no dedicated analyst yet)
- Contributing to product thinking and commercial goals—engineers here aren't siloed
What They Need
- 2-3+ years building production-grade data systems in fast-paced environments
- Solid experience with modern data stack (ELT pipelines, data warehouses, semantic layers, LLM integration)
- Strong SQL and comfortable with dbt for data transformation
- Product-minded—you care about outcomes, ask "why", and understand user context
- Self-directed with a bias for execution—you can scope work, sense-check approaches, and ship without hand-holding
- Balance speed with quality—know when to be scrappy, when to go deep
The Stack
Data: Dagster, Airbyte (custom connectors), dbt, BigQuery, Cube, Metabase, PostgreSQL/Supabase AI: LLMs via Google Vertex & Azure AI Foundry for document extraction Rest of stack: TypeScript, Next.js, Node.js
Bonus Points
- Fintech or payments experience
- Healthcare domain knowledge
Why This One's Different
- Early-stage impact—shape the tech, product, and company direction
- Team of repeat founders who move fast and promote based on impact, not tenure
- Proper on-site setup in a private office in Paddington (Merchant Square)—they believe in in-person collaboration early on
- Applying fintech innovation to genuinely high-impact problems
- Expectations are high, but so is the growth opportunity
If you want to building something that actually matters—and want proper ownership in an early-stage environment—this is worth a look.
