Senior Data Engineer - Commodities & Energy Trading
1 day ago
London
Senior Data Engineer - Commodities & Energy Trading Skills, Experience, Qualifications, If you have the right match for this opportunity, then make sure to apply today. £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, • 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, • 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), • 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 learningWhy Join? xrnqpay, • 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 #aaon