Data Engineer (Commodities)
Summary
Builds high-performance data systems for a global commodities trading firm, ingesting complex datasets (weather, freight, satellite) and enabling rapid research pipelines with Python, SQL, and modern data tools.
For Data Engineers working in commodities who are keen to build high-performance data systems at a global Tier-1 systematic market maker.
Hyphen is working with a global Tier-1 quantitative trading firm looking to hire a Data Engineer to build production-grade data systems to ingest complex, external commodity datasets.
The Opportunity:
- Designing ingestion frameworks for alternative and market-adjacent commodities data (weather, freight, satellite, regulatory, demand, surveys, etc.)
- Building fast-turnaround research pipelines so new datasets can be evaluated in days, not months
- Architecting storage models that allow rapid hypothesis testing without breaking production integrity
- Working shoulder-to-shoulder with traders to reduce data friction in signal discovery
- Balancing speed vs. robustness — knowing when to prototype and when to productionise
- Leveraging modern AI tooling to accelerate both development and data enrichment
What our ideal candidate possesses:
- Experience engineering commodities market data ingestion pipelines (for energy, metals, freight, weather, satellite, demand, physical flows, etc.) using Python and SQL .
- Demonstrable system design capability
- Strong familiarity with data tools such as Airflow, Spark, distributed compute, or similar modern data stacks
If you fit the requirements and you're keen to join a Tier-1 commodities market maker on their mission to better quality data, apply now or email me directly at (HIDDEN TEXT) with your CV.