Data Engineer
| Dyddiad hysbysebu: | 18 Rhagfyr 2025 |
|---|---|
| Oriau: | Llawn Amser |
| Dyddiad cau: | 17 Ionawr 2026 |
| Lleoliad: | London, UK |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | Marchmont Capital Holdings Ltd |
| Math o swydd: | Parhaol |
| Cyfeirnod swydd: |
Crynodeb
The Job: We ingest millions of data points from XBRL filings and map them into a proprietary database alongside unstructured data from unpredictable sources. You will work directly with the founder and the technical team to maintain and scale this ingestion pipeline, ensuring our product stays grounded in deterministic financial facts.
What you’ll do:
Pipeline: Build, manage and extend our Python-based ingestion engine that processes XBRL data into PostgreSQL.
Data Integrity: Implement "fail-fast" validation logic to ensure accuracy in our financial database.
AI Support: Assist in building the retrieval logic that powers our AI architecture.
What we’re looking for:
Cultural alignment: You will work closely with the founder in person for long hours; alignment on personality and strategic vision is non-negotiable and the most important consideration.
The Stack: Strong Python skills and experience with PostgreSQL/pgvector. Exposure to Neo4j or other graph databases is a plus.
Domain curiosity: You don’t need to be a CFA, but you should be interested in how financial markets work and how data is used to drive an investment decision.
Background: 1-2 years of experience or a graduate with a portfolio of data-heavy projects (Web scraping, ETL pipelines, or RAG applications).
What you’ll do:
Pipeline: Build, manage and extend our Python-based ingestion engine that processes XBRL data into PostgreSQL.
Data Integrity: Implement "fail-fast" validation logic to ensure accuracy in our financial database.
AI Support: Assist in building the retrieval logic that powers our AI architecture.
What we’re looking for:
Cultural alignment: You will work closely with the founder in person for long hours; alignment on personality and strategic vision is non-negotiable and the most important consideration.
The Stack: Strong Python skills and experience with PostgreSQL/pgvector. Exposure to Neo4j or other graph databases is a plus.
Domain curiosity: You don’t need to be a CFA, but you should be interested in how financial markets work and how data is used to drive an investment decision.
Background: 1-2 years of experience or a graduate with a portfolio of data-heavy projects (Web scraping, ETL pipelines, or RAG applications).