Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Engineer

Harnham
City of London
1 week ago
Create job alert

This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.


Base pay range

Direct message the job poster from Harnham


Senior Recruitment Consultant - Software and Data Engineering @ Harnham

Hybrid (3 Days Per Week) - London


Up to £80,000 + Benefits


We’re partnering with one of the most exciting InsurTech scale‑ups in the market – a company transforming how brokers and insurers exchange risk, already processing over $150m in premium and targeting $1B by 2027. They’re looking for a Senior Data Engineer (3-5 years' experience) to help scale their modern data platform as they continue rapid growth.


What you’ll do:

  • Build and maintain scalable, automated, reliable data pipelines across a modern cloud stack
  • Extend and improve a cutting‑edge Data & Analytics Platform supporting mission‑critical insurance products
  • Implement data quality checks, observability metrics and troubleshooting processes
  • Manage cloud resources via Infrastructure‑as‑Code
  • Ensure strong data security, access control, and governance
  • Work closely with commercial, analytics and engineering teams to deliver high‑quality data products

What you’ll bring:

  • 3-5 years' experience as a Data Engineer
  • Strong SQL and Python skills
  • Proven experience building modern ETL/ELT pipelines (dbt experience ideal)
  • Experience with data orchestration tools (Prefect preferred)
  • Understanding of data modelling, especially event‑driven architectures
  • Knowledge of modern data engineering development practices

Nice to have:

  • Background in InsurTech/FinTech or regulated industries
  • Experience with Docker, containerisation, and IaC tools
  • Work at the forefront of a market undergoing a "Big Bang" digital transformation
  • Join a smart, curious, collaborative team backed by deep insurance and technology expertise
  • Build systems that will scale to handle millions of dollars of real‑world insurance risk
  • Huge growth opportunity as the company scales rapidly

Seniority level

Mid‑Senior level


Employment type

Full‑time


Job function

Information Technology


Industries

Technology, Information and Internet


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.