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

Apply Now

AI Cloud Data Architect

London
8 months ago
Applications closed

Related Jobs

View all jobs

Junior Data Engineer

Principal Cloud Data Engineer - Lead Data Platform & AI

Senior Azure Data Engineer

Principal Data Engineer

Senior Data Engineer

Senior Data Engineer

Cloud Data Architect, Azure, PaaS, OO, ETL, Microsoft, Mainly Remote

Cloud Data Architect required to work for a fast growing business based in Central London. However, this will be practically remote – there will be some travel to the Central London offices, and as it is a global role, there will be some global travel from time to time. However, ALL travel and accommodation expenses will be paid.

We need an experienced Cloud Data Architect, who is well rounded, highly experienced and has good, solid Microsoft Stack skills. Read on for more details…

Key responsibilities:

  • Architecting and designing solutions in a cloud native data environment

  • Guide and coach the development teams and data engineers around architectural data topics

  • Adhere and contribute to internal Secure Development policies and play a proactive role in making sure application are secure by design

  • Adhere to company Change Management procedures

  • Adhere and contribute to the company architecture standards and guidelines

  • Communicating effectively with the Enterprise Architect, Product Manager, Senior manager Technology Services, Portfolio managers, Global IT and other key stakeholders

  • Support Level 3 investigations

  • Provide leadership to other team members working in an Agile environment

    Experience required:

  • Ideally a degree in Computer Science or similar (this is not essential)

  • Expert skill level with circa 3-4 years' experience with the following technologies:

    • Azure PaaS Data Services

    • Object Oriented Analysis and Design

    • CI/CD and source control

    • ETL techniques and principles

    • Data modelling

    • Master Data Management

    • Data Visualization

  • Experienced in designing and implementing data platform, reporting and analytics solutions in the Microsoft Azure ecosystem

  • Familiarity with Agile Project Management and methodologies desired

  • Able to exercise independent judgement and take action on it

  • Excellent analytical and creative problem-solving skills

  • Excellent listening, written, and oral communication skills

  • Strong relationship, interpersonal, and team skills

  • Highly self-motivated and directed

  • Experience working in a team-oriented, collaborative environment

    This is a great opportunity and salary is dependent upon experience. Apply now for more details

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.

Jobs

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.

Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.