Senior Engineer, Commodities Technology
The commodities data engineer turns vendor and alternative feeds into inputs for investment decisions. Work spans ingestion, data models, analytical storage and dependable services for traders and researchers.
What you’d work on
Our reading of the posting: what a new hire in this role would most likely spend their first months on.
- Integrate weather, tracking and vendor datasets
- Define consistent schemas and quality controls
- Improve query speed, memory use and streaming performance
- Investigate data failures and strengthen monitored workflows
What they ask for
Required
- Five or more years of data engineering
- Python and SQL
- Analytical database experience
- Java, Kotlin or another systems language
- Streaming platforms
- Kubernetes and release tooling
- Production debugging
Preferred
- Energy and commodity-market exposure
- Education
- No degree requirement is specified.
- Experience
- 5+ years owning data platforms, distributed systems or backend services.
- Languages and tools
- Markets
- commodities
How to prepare
- Build a monitored commodity-data ingestion pipeline
- Compare analytical-store query plans on a large dataset
- Explain recovery and validation for delayed vendor feeds
What to study
- Quantitative Data Engineering
- Python for Quantitative Finance
- Trading Systems and Low-Latency Infrastructure
The HFT Quant Developer roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on Balyasny Asset Management’s site before applying: requirements, location and pay can change after we check them.
View the posting on Balyasny Asset Management’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Balyasny Asset Management and doesn’t handle applications.