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

Apply Now

Head of Data Engineering

Harnham
London
2 weeks ago
Create job alert
Overview

HEAD OF DATA ENGINEERING – HYBRID – LONDON

THE COMPANY
This high-growth, product-led scale-up is redefining how data powers decision-making in the mobility and financial services space. By processing vast streams of behavioural and location data, the business delivers real-time insights that shape pricing, onboarding, and risk models. As they scale their data capabilities, this role will directly shape the architecture, tools, and team that underpin their most critical data products.

THE ROLE

As Head of Data Engineering, you will lead the strategic direction, architecture, and delivery of a modern, scalable data platform. You’ll oversee the ingestion, transformation, and processing of large-scale datasets, enabling high-performance analytics, real-time insights, and advanced ML use cases. This is a hands-on leadership role where you’ll grow and mentor a talented team, modernise tooling, and define best practices across the engineering organisation.

Specifically, you can expect to be involved in the following:

  • Leading and mentoring a team of Data Engineers
  • Designing and evolving a scalable, reliable data platform using AWS, Snowflake, Apache Spark, Airflow, dbt, Python, and SQL
  • Overseeing ingestion of high-volume signal data and integrating external data sources
  • Driving adoption of modern engineering practices—CI/CD, testing, infrastructure-as-code, and data governance
  • Partnering with other data leaders to deliver business-aligned solutions
  • Leading technical initiatives such as re-architecting pipelines, implementing real-time processing, and modernising platform tooling
SKILLS AND EXPERIENCE

The successful Head of Data Engineering will have the following skills and experience:

  • 5+ years as a Data Engineer and 2+ years in a technical leadership or management role
  • Proven experience designing scalable data architectures and building robust pipelines
  • Strong knowledge of AWS, Snowflake, orchestration (Airflow), transformation (dbt), and large-scale processing (Spark or equivalent)
  • Proficiency in Python and SQL
  • Track record of delivering in fast-paced, product-led environments (start-up/scale-up experience preferred)
  • Strong leadership skills with the ability to grow and inspire high-performing teams
BENEFITS

The successful Head of Data Engineering will receive the following benefits:

  • Annual bonus
  • Share options in a high-growth business
  • Hybrid working: 1 day per week onsite in central London (Bank/Monument)
  • Private health and life cover
  • Generous holiday allowance and pension scheme
  • Opportunity to shape the data strategy and platform of a scaling, data-led business
HOW TO APPLY

Please register your interest by sending your resume/CV to Joana Alves via the Apply link on this page.


#J-18808-Ljbffr

Related Jobs

View all jobs

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

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.