Senior Data Engineer

🔥 Senior / Lead Data Engineer – Databricks / Spark (High-Performance Platform) £850 p/d OUTSIDE IR35 (higher for Lead) 12-month rolling (multi-year programme) 1 day/week – St Paul's, London We're hiring a Senior & Lead Data Engineer to build a Databricks lakehouse platform in a high-performance, business-critical Front office Risk trading environment. This is a hands-on engineering role focused on building and optimising large-scale distributed data systems. This is a highly technical team operating at scale, we're looking for engineers with deep data engineering expertise, strong low-level Spark knowledge, and experience building high-performance systems using modern Databricks and AI-driven platforms. This is working for a Front office Risk Data team, so you MUST have experience working closely with Front/middle office users and have good domain knowledge covering Market and credit Risk and derivatives . What you'll do Defining technical approach for migrating historic data from existing SQL server instances to Databricks then keeping that data flow on a daily/intraday basis. Building pipelines from bronze to silver/gold/platinum Curation of data products in the market risk, credit risk and historic market data domains. Build and optimise Spark pipelines on Databricks Develop a lakehouse platform (Medallion architecture) Own data modelling, architecture, and pipeline design Work with large-scale data (TB–PB) Drive performance, scalability, and reliability in production What we're looking for

• Strong experience running Spark workloads in production
• Proven ability to optimise Spark at scale (Tb/PB datasets)
• Solid Python (Scala beneficial, not essential)
• Experience with data modelling and lakehouse architecture
• Ability to debug and improve performance in distributed systems Important
• Must have recent, hands-on Spark experience
• Databricks strongly preferred (not essential if Spark depth is very strong)
• Experience supporting AI/ML or advanced analytics platforms is a big plus
• Financial services / trading exposure
• Experience in performance-critical environments Not a fit if
• Primarily BI / reporting focused
• Spark used only at small scale or outside production
• No experience with performance optimisation in distributed systems Stack Databricks (Azure), Spark, Delta Lake, Python (+ Scala optional) Bottom line We're looking for engineers who can design, build, and optimise Spark-based systems at scale and operate effectively in a performance-critical environment from day one.