CipherTek Recruitment

Senior Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer focused on building a Databricks lakehouse platform in a high-performance trading environment. Contract length is 12 months at £850 p/d. Key skills include Spark, Databricks, Python, and experience with large-scale data systems.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
1040
-
🗓️ - Date
April 28, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Outside IR35
-
🔒 - Security
Unknown
-
📍 - Location detailed
City Of London, England, United Kingdom
-
🧠 - Skills detailed
#AI (Artificial Intelligence) #ML (Machine Learning) #Azure #Datasets #Databricks #Delta Lake #Spark (Apache Spark) #Python #Data Engineering #Scala #BI (Business Intelligence)
Role 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 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. . 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.