Senior Data Engineer at CipherTek Recruitment, City Of London, £850 per day

🔥 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 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.

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What you’ll do

• 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

Nice to have

• 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.