Data Engineer

Data Engineer (Commodities / Pricing Analytics) – London (Hybrid) | Up to £175,000 + Bonus

We are seeking a highly capable Data Engineer to join a high-performing, technology-driven commodities trading environment. This is a rare opportunity to work at the intersection of data engineering, quantitative research, and pricing analytics, supporting mission-critical trading and AI initiatives.

💼 The Opportunity

You will play a central role in building and maintaining scalable, high-performance data infrastructure that powers pricing, trading analytics, and machine learning models across global commodities markets.

The work is fast-paced, technically challenging, and highly impactful—supporting both traders and data scientists working on systematic trading and predictive analytics.

You will be joining a team that is actively investing in AI capabilities, cloud architecture, and next-generation data platforms, with significant learning and development opportunities.

📊 Salary & Levels

🔹 Junior-to-Mid Level Data Engineer – Up to £120,000

• Strong technical foundation with ambition to grow
• Hands-on builder mindset with strong Python/SQL skills
• Potential to evolve into a future team lead

🔹 Senior Data Engineer – up to £175,000

• Deep technical expertise with proven leadership in data engineering
• Experience owning complex data platforms and pipelines
• Ability to lead technical direction and mentor others

Both roles come with a bonus and strong long-term progression potential.

🧠 Key Technical Skills

• Advanced SQL (Postgres strongly preferred)
• Strong Python development (Pandas essential)
• Experience with commodities pricing / financial markets
• Building and maintaining data pipelines (ETL/ELT, streaming)
• Working with time-series / analytical databases (e.g. Redshift, ClickHouse)
• Experience with Docker and containerised environments
• Git-based workflows and collaborative development

⚙️ Responsibilities

• Design, build, and maintain scalable data pipelines (structured & unstructured data)
• Ingest data from multiple sources (APIs, scraping, streaming, external feeds)
• Cleanse, transform, and structure data for analytics and trading use cases
• Support pricing models, forecasting tools, and machine learning workflows
• Maintain and optimise data storage systems (data lakes, warehouses, databases)
• Develop internal data APIs and reusable Python tooling
• Support automation of analytical and predictive workflows
• Work closely with Data Scientists, Quants, and Traders
• Contribute to documentation and knowledge sharing across data systems
• Build dashboards and visualisations where needed

🌐 Desirable Experience

• Exposure to commodities trading or energy markets
• Experience interfacing with traders or quant teams
• Cloud experience (AWS preferred: S3, Lambda, Athena, EMR, etc.)
• CI/CD and Infrastructure-as-Code (CDK, CloudFormation)
• Big data tools (Spark, Databricks, Hadoop, Parquet, etc.)
• API development and data integration (REST, web APIs)
• Interest in AI/ML systems and modern data tooling
• Experience mentoring or leading engineers (for senior track)

🚀 Why This Role?

• Opportunity to work on high-impact pricing and trading systems
• Direct exposure to advanced commodities analytics and quant workflows
• Involvement in building a new AI-focused task force
• Strong culture of learning, experimentation, and technical ownership
• Significant bonus potential and long-term progression opportunities
• Collaborative, high-calibre engineering and research environment