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

£850 per day

Contract Description

🔥 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

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What you’ll do


  1. Defining technical approach for migrating historic data from existing SQL server instances to Databricks then keeping that data flow on a daily/intraday basis.
  2. Building pipelines from bronze to silver/gold/platinum
  3. Curation of data products in the market risk, credit risk and historic market data domains.
  4. Build and optimise Spark pipelines on Databricks
  5. Develop a lakehouse platform (Medallion architecture)
  6. Own data modelling, architecture, and pipeline design
  7. Work with large-scale data (TB–PB)
  8. 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.