Fabric Data Engineer

London
4 months ago
Applications closed

Related Jobs

View all jobs

Fabric Data Engineer

Fabric Data Engineer - Outside IR35 - Hybrid

Azure Data Engineer (Microsoft Fabric)

Azure Data Engineer Microsoft Fabric

Azure Data Engineer Microsoft Fabric

Azure Data Engineer Microsoft Fabric

A well-established business in Brentford is seeking an experienced BI Developer to join their BI & Data Team as they embark on a major transformation journey, moving from legacy systems towards a modern Microsoft ecosystem built on Azure and Fabric.

The team operates mostly remotely, with office collaboration up to once per week alongside the wider BI & Data team and other business stakeholders.

This is a pivotal role where you'll take ownership of the migration, design the architecture, and ensure the new set-up supports analytics, forecasting, and AI enablement.

Key responsibilities will include:

Designing and delivering scalable BI solutions using Microsoft Fabric
Building and managing data pipelines with OneLake, Dataflows Gen2, and Data Factory
Developing semantic models in Power BI and integrating with DirectLake or Warehouse datasets
Optimising data models for performance and reusability
Supporting governance, security, and compliance best practices in a modern data platform
Tooling for migration and reconciliation of data from legacy systems or acquisitions
Providing technical support and hands-on data engineering across the full stackWe are looking for:

Strong experience as a BI Developer, Data Engineer, or similar
Hands-on experience with Microsoft Fabric (essential)
Proven expertise with Azure Data services (e.g. Data Factory, OneLake, Synapse, etc.)
Solid background in database technologies (SQL), and reporting tools (Power BI)
Excellent communication skills to work across technical and non-technical teams
Experience with migration projects (e.g., moving from legacy BI to Fabric) is desirable
Knowledge of governance and security within Microsoft Purview is a plusYou will be rewarded with:

Salary up to £60,000 depending on experience
Flexible remote working, with occasional office collaboration
Opportunity to play a key role in a major data transformation projectIf you're ready to make an impact and help shape the future of BI and analytics for a forward-thinking business, apply today

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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.