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

Apply Now

Head of Data Engineering

City of London
3 weeks ago
Create job alert

Head of Data Engineering - Azure & Databricks - Remote - Up to £100,000

A forward-thinking and nationally recognised organisation, known for its commitment to innovation and data-driven decision-making, is seeking a Head of Data Engineering to lead its growing data function. With a strong culture of collaboration, investment in cutting-edge technology, and a clear roadmap for digital transformation, this company offers an exciting environment for technical leaders to make a real impact.

Key Responsibilities:

Lead and mentor a team of data engineers, fostering a culture of innovation and excellence.
Architect and implement scalable data solutions using the Azure tech stack and Databricks.
Collaborate with cross-functional teams to align data initiatives with business goals.
Maintain hands-on involvement in technical delivery where needed, ensuring best practices are followed.Requirements:

Proven experience in leading data engineering teams.
Strong expertise in Azure Data Services (e.g., Data Factory, Synapse, Azure Datalake) and Databricks.
Comfortable balancing strategic leadership with occasional hands-on technical work.
Excellent stakeholder management and communication skills.Benefits:

Competitive salary up to £100,000.
Opportunity to shape the data landscape of a forward-thinking organisation.
Discretionary Bonus.
And more

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 - Preston

Head of Data Engineering - Preston

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

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.