Data Engineer (Commodities)
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.
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.