Senior Data Engineer - Commodities & Energy Trading

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, 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, 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

• 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