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

Apply Now

Data Engineering Lead

London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineering Lead — Azure & Databricks (Remote)

Data Engineering Lead - Azure & Databricks | Remote

Remote Data Engineering Lead - Azure & Databricks

Remote Data Engineering Lead - Azure & Databricks

Senior Data Engineering Lead - Cloud Pipelines & Governance

Data Engineering Director

Data Engineering Lead

Salary: Up to £95,000 + Bonus

I am working with a technology driven organisation who are leaders in their field that are delivering some of the world's most innovative projects in their space. With a strong focus on innovation, sustainability and data-driven decision-making, they are investing heavily in their digital transformation journey.

As part of this growth, they are looking to bring on a Data Engineering Lead to shape and optimise their hybrid Azure/Databricks data platform. This is a strategic and hands-on role where you will lead the development of scalable data solutions and mentor a team of BI Developers and Engineers.

You will be part of a collaborative environment that values technical excellence, continuous learning and inclusive leadership.

In this role, you will be responsible for:

Leading a technical team to deliver dashboards and data products aligned with business needs.
Designing and developing robust data pipelines using Azure Data Factory, Databricks, and SQL.
Architecting a scalable, high-performance data infrastructure using medallion architecture principles.
Optimising hybrid cloud environments for performance, scalability and cost-efficiency.
Implementing data governance, quality standards, and security protocols.
Translating technical concepts into actionable insights for stakeholders across the business.To be successful in this role, you will have:

Proven experience in data engineering using Azure, Databricks, and SQL.
Strong leadership and mentoring skills within data or BI teams.
Expertise in ETL orchestration and data architecture in an Azure cloud environment.
Excellent communication and stakeholder engagement skills.Some of the package/role details include:

Salary up to £95,000
Discretionary annual bonus
Hybrid working (3 days) in modern, central London location
8% company pension contribution
25 days annual leave + holiday buy options
Private medical cover, virtual GP, and employee assistance programme
Enhanced parental leave and flexible benefitsThis is just a brief overview of the role. For the full details, simply apply with your CV and I will be in touch to discuss it further

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.