AI Data Engineer Trading Analytics

We’re supporting a client looking to expand their AI and data capability within a front-office trading environment.

This is a highly hands‑on role for a senior engineer who can work directly with traders and analysts to build AI‑driven analytics on top of large‑scale market and fundamentals data. You’ll be operating in a fast‑paced environment where speed of delivery, strong communication and technical depth are all key.

The role would suit someone with a strong data engineering background who has also moved into applied AI and enjoys working close to the business.

This role is inside IR35, initial 6 months, £700-800pd and 2-3 days per week onsite in Central London.

• Develop and deliver AI‑powered analytics tools to support trading decisions (e.g. forecasting, correlations, scenario analysis)
• Build and optimise scalable data pipelines using Databricks and Spark across large, complex datasets
• Work directly with traders and analysts to turn open‑ended questions into actionable, data‑driven solutions
• Apply statistical and analytical techniques to market and time‑series data to generate meaningful insights
• Design and implement LLM‑driven workflows, including prompt engineering, orchestration and integrations
• Ensure solutions are production‑ready, with appropriate testing, monitoring, and documentation
• Continuously iterate with end‑users to refine and improve outputs in a live trading environment

• Strong hands‑on experience with Databricks and Spark (including PySpark and SQL)
• Proven background in data engineering, including pipeline development, data modelling and performance optimisation
• Solid grounding in statistics, econometrics or data science, particularly within time‑series data
• Experience building or deploying AI/LLM‑based solutions in a production setting
• Strong understanding of software engineering best practices (version control, testing, CI/CD)
• Ability to work directly with business stakeholders and communicate technical outputs clearly
• Experience working at pace, iterating quickly from prototype through to production

• Exposure to commodity or financial trading environments
• Understanding of market data, pricing, or supply and demand fundamentals
• Familiarity with infrastructure tooling such as Terraform or MLflow
• Experience with vector databases, feature stores or data governance frameworks
• Knowledge of data security, lineage and compliance considerations

• Hybrid setup with close collaboration alongside trading teams
• Fast‑paced, iterative delivery model with a strong focus on practical outcomes
• Emphasis on building robust, scalable solutions that can transition from prototype to production
• Strong engineering standards around testing, deployment, and reliability

Please apply below directly if interested!