Data Engineer

Tenth Revolution Group
London, United Kingdom
Today
£60,000 – £90,000 pa

Salary

£60,000 – £90,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
Hybrid
Seniority
Senior
Education
Degree
Posted
30 Apr 2026 (Today)

Benefits

Hybrid working with a central London office High-impact role with real ownership and autonomy Modern cloud and data technology stack Strong exposure to senior London Market stakeholders Supportive, collaborative engineering culture Clear long-term progression within the data function

Data Engineer - Insurance & London Market - London (Hybrid) - Python, PySpark, Databricks, Snowflake - Up to £90,000

This is an opportunity to join a business right in the middle of a major data transformation within the London Insurance Market. They're investing in modern, cloud-native platforms and are looking for senior engineers who can shape solutions end-to-end, not just deliver pre-defined tasks.

Data sits at the heart of underwriting, pricing, claims, and reinsurance decisions here, which means your work will be highly visible and genuinely impactful. The environment is collaborative, engineering-led and focused on doing things properly.

If you're looking for a role where you can lead technically, stay hands-on, and work on complex London Market data, this is a great move.

You Will Work With

  • Designing and building cloud-based data platforms using medallion architecture (Bronze / Silver / Gold)
  • Developing batch and near real-time data pipelines
  • Engineering scalable pipelines using Python and PySpark on Databricks and/or Snowflake
  • Integrating data from PAS, claims systems, broker platforms, third-party providers, and market feeds
  • Ensuring high standards of data quality, reconciliation, lineage, and auditability
  • Working closely with Underwriting, Actuarial, Finance, and Regulatory stakeholders
  • Carrying out code reviews, setting engineering best practice, and mentoring junior engineers
  • Supporting CI/CD pipelines and Git-based delivery models
  • Contributing to modern engineering practices, including AI-assisted software development, in a governed way

Benefits

  • Salary up to £90,000 (depending on experience)
  • Hybrid working with a central London office
  • High-impact role with real ownership and autonomy
  • Modern cloud and data technology stack
  • Strong exposure to senior London Market stakeholders
  • Supportive, collaborative engineering culture
  • Clear long-term progression within the data function

Key Experience

  • Proven experience as a Senior Data Engineer within Insurance, ideally the London Market
  • Hands-on expertise with:
    • Python & PySpark
    • Databricks and/or Snowflake
    • Cloud platforms (Azure, AWS, or GCP)
  • Strong understanding of:
    • Medallion architecture
    • Batch and streaming pipelines
    • Data modelling for analytics and reporting
  • Solid domain experience across:
    • Lloyd's Syndicates
    • Delegated Authority / Bordereaux
    • Reinsurance and Ceded Reinsurance
    • Underwriting, pricing, and claims data
  • Confident engaging senior technical and non-technical stakeholders

Interested?

Apply now or send your CV directly

Related Jobs

View all jobs

Data Engineer

Noir Switzerland, United Kingdom
£87,291 – £113,478 pa Hybrid

Data Engineer

Lynx Recruitment London, United Kingdom
£40,000 – £85,000 pa On-site

Data Engineer

Gleeson Recruitment Group Birmingham, United Kingdom
£65,000 – £75,000 pa On-site

Data Engineer

Sanderson Cardiff, Cymru / Wales, CF10 2AF, United Kingdom
£60,000 – £72,000 pa Hybrid

Data Engineer

hireful Exeter, United Kingdom
£50,000 – £55,000 pa Hybrid

Data Engineer

Robert Walters Manchester, United Kingdom
£55,000 – £60,000 pa Hybrid

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Engineering Jobs in the UK (2026 Guide)

Advertising data engineering jobs in the UK requires a different approach to most technical hiring. Data engineers occupy a distinct discipline that sits between software engineering, data science and cloud infrastructure — and the strongest candidates identify firmly with the data engineering community rather than with adjacent roles. General job boards consistently conflate data engineering with data analysis, data science and BI development, producing high application volumes but low candidate quality for specialist pipeline and platform roles. This guide, published by DataEngineeringJobs.co.uk, covers where to advertise data engineering roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.