Job Description - Senior Data Engineer - Commodities & Energy Trading
£Up to £175,000 GBP
Competitive Bonus
Hybrid WORKING
Location: Central London, Greater London - United Kingdom Type: Permanent
Senior Data Engineer - Commodities & Energy Trading
London | Permanent | Hybrid Working
Our client is a global commodities and energy trading organisation operating an asset-light, highly diversified business model. The firm combines advanced analytics, proprietary technology, and robust risk management to support trading, optimisation, and risk-management decisions across energy and commodities markets.
As a Senior Data Engineer, you will join a highly technical Data, AI & Analytics function responsible for building the data platforms that underpin trading, quantitative research, predictive analytics, and machine-learning use cases. This is a hands-on role with ownership across data ingestion, transformation, storage, and distribution, working closely with Data Scientists, Traders, and technology teams.
You'll have the opportunity to:
Build and maintain scalable data pipelines supporting trading and analytics use cases
Ingest structured and unstructured data from diverse internal and external sources
Support predictive analytics, systematic trading, and machine-learning workloads
Partner closely with Data Scientists and Trading teams to deliver high-quality datasets
Contribute to cloud-native data platforms using modern engineering practices
Drive improvements in data quality, performance, and self-service capabilities
Your Responsibilities
As a Senior Data Engineer, you will:
Design and implement data ingestion pipelines using ETL, streaming, scraping, and batch approaches
Clean, enrich, and transform datasets for analytical and operational consumption
Persist data across databases, warehouses, and data lakes
Distribute data internally via APIs, Python packages, and direct querying
Maintain and enhance production data pipelines and databases
Support post-processing automation, including analytics, models, and visualisation workflows
Enable Data Scientists through shared libraries, cloud resources, and documented data access
Maintain knowledge bases covering data sources, pipelines, and usage
Key Requirements
As a Senior Data Engineer, you should have:
Strong engineering background in Data Engineering, Computer Science, or similar
Experience working in commodities, energy trading, or financial markets environments
Advanced Python skills, including extensive use of Pandas
Experience with analytical or time-series databases (e.g. Redshift, ClickHouse)
Hands-on experience with Docker and containerised workloads
Experience with Git and modern DevOps practices
Practical experience deploying infrastructure on AWS using IaC (e.g. CDK, CloudFormation)
A proactive, ownership-driven mindset with strong problem-solving skills
You will gain exposure with:
Working as a Senior Data Engineer, you will gain exposure to:
Direct collaboration with Traders and quantitative teams
Cloud-native data platforms supporting real-time and batch processing
Big-data and distributed processing tools
AWS services such as S3, Lambda, Athena, EMR, Kinesis, and EC2
Advanced analytics, visualisation, and data-science workflows
Emerging technologies across AI and machine learning
Why Join?
Work on data platforms that directly support trading and optimisation decisions
Own data engineering solutions end-to-end in a high-impact environment
Operate in a technically deep, collaborative engineering culture
Competitive compensation with performance-linked bonus
Hybrid working model supporting flexibility and collaboration
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