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

Apply Now

Lead Data Engineer

Searchability®
London
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Data engineer

Lead Data Engineer - Microsoft Fabric - Hybrid - £75k

Lead Data Engineer

Lead Data Engineer - Preston

Lead Data Engineer - Preston

Lead Data Engineer - Preston

Lead Data Engineer


  • Opportunity for a Lead Data Engineer to join a market leading Software House company in London
  • Salary up to £150,000 + fantastic benefits including our share options, collaborative working culture and exciting growth opportunities andmore
  • Apply online or contact Chelsea Hackett via


WHAT WILL YOU BE DOING?

As a Lead Data Engineer, you’ll take ownership of the entire data function — designing, scaling, and optimising the data platform that powers AI-driven products and insights. You’ll lead a small team of data engineers, set technical direction, and shape the company’s data strategy while staying hands-on with modern tooling across pipelines, cloud infrastructure, and data architecture.


WHO WE ARE:

As a recently founded company we develop technology to modernise workflows in the pet care sector. Our platform uses automation and AI to simplify routine tasks, reduce administrative burdens, and improve communication, allowing our professionals to focus more on care. With early funding and industry partnerships, we are gaining traction as an emerging player bringing efficiency and innovation to a traditionally outdated space.


OUR BENEFITS:

  • Private medical insurance
  • Life insurance
  • Share options
  • Exciting growth opportunities
  • And More..


LEAD DATA ENGINEER – ESSTENTIAL SKILLS

  • Proven experience as a Senior or Lead Data Engineer in a fast-scaling tech or data-driven environment
  • Strong proficiency in Python (or Scala/Java) and SQL
  • Deep experience with data pipeline orchestration tools (Airflow, dbt, Dagster, Prefect)
  • Strong knowledge of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift)
  • Hands-on experience with streaming technologies (Kafka, Kinesis, or similar)
  • Solid understanding of data modelling, governance, and architecture best practices
  • Familiarity with machine learning pipelines or AI model integration



TO BE CONSIDERED…

Please either apply by clicking online or emailing me directly . By applying to this role, you give express consent for us to process and submit (subject to required skills) your application to our client in conjunction with this vacancy only.

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.