Senior Data Engineer - Microsoft Fabric

Peaple Talent
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer (AWS, Airflow, Python)

Senior Data Engineer (Microsoft Fabric)

Senior Data Engineer - (Python & SQL)

Senior Data Engineer | Microsoft Fabric🧵 | £70,000 - £75,000


We’re working with a growing consultancy known for delivering modern, scalable data solutions. Their work sits at the intersection of strategy, engineering and innovation, empowering organisations to unlock value through cutting-edge Microsoft technologies.


As part of their continued growth, they’re now seeking a Senior Data Engineer to take a pivotal role in delivering enterprise-grade data solutions, with a strong focus on Microsoft Fabric and the wider Azure ecosystem.


What you’ll do:

  • Lead the design and implementation of data platforms powered by Microsoft Fabric
  • Guide delivery teams through complex builds across cloud-native architectures
  • Bridge the gap between hands-on engineering and technical strategy
  • Collaborate closely with clients and internal stakeholders to translate needs into scalable solutions


What you bring:

  • Deep experience with Microsoft Azure, particularly around data services
  • Proven track record delivering with tools such as Fabric, Databricks or Snowflake
  • Proficiency in SQL, Python, and modern data engineering patterns
  • Leadership experience within engineering or delivery teams
  • A consultancy mindset - adaptable, curious, and client focused


Location & Flexibility:

Primarily remote, with periodic team sessions in London


Why consider this?

💰Salary: £70,000-£75,000

⭐Bonus up to 10%

🚀Be part of one of the first waves delivering at scale on Microsoft Fabric

🤝Work in a culture that values learning, innovation, and trust

📈Access to advanced training, cloud certifications, and fast-paced career progression

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.