Azure Data Engineer

Cloud Decisions
Leeds
9 months ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer | Microsoft Solutions Partner | UK-wide (Remote)

Up to £75,000 + 15 Bonus


Ready to level up your career as an Azure Data Engineer? Good, because this opportunity is serious about data and needs someone equally committed. This ambitious Microsoft Solutions Partner specialises in Azure and advanced cloud solutions, and they're looking for someone sharp, capable, and passionate about data to help drive their growth.


The Essentials:

  • Role:Azure Data Engineer
  • Location:UK-wide remote, with VERY occasional travel to offices and client sites
  • Employment:Permanent, Full-time


What You'll Actually Be Doing:

  • Designing, developing, and deploying robust Azure data solutions including ETL pipelines, data warehouses, and real-time analytics. No fluff, just solid engineering.
  • Turning complex client requirements into clear, scalable Azure solutions alongside experienced Architects and Data & AI Practice Leads.
  • Building strong relationships with clients—clear communication and reliability matter.
  • Continuously expanding your expertise—this isn’t a stagnant role; they're looking for someone driven to stay at the forefront of technology.


Who They're Looking For:

  • At least 3 years of meaningful experience with Azure Data platforms (Azure Synapse, Databricks, Data Factory, Data Lake, etc.).
  • Azure certifications highly valued: Azure Data Engineer Associate, Azure Solutions Expert, Azure AI Engineer.
  • Confident communicator who can clearly translate technical information to stakeholders at all levels.
  • Independent and proactive, you see opportunities and take initiative without waiting to be asked.


Key Tech Experience Needed:

  • Azure Data technologies (Synapse, Databricks, Data Factory, Data Lake, Microsoft Fabric)
  • Azure DevOps, Git
  • Stream Analytics, Event Hubs
  • T-SQL, Python
  • Power BI expertise, including DAX


What's On Offer:

  • Comprehensive, uncapped training—your growth is fully supported.
  • Meaningful benefits (Private Medical, Income Protection, Gym Discounts—perks you'll genuinely use).
  • A culture that genuinely values and rewards good work.


This organisation is building something impactful. If you're the right fit, you'll know it.


Interested? Apply here or get in touch with Oli Ridley via LinkedIn

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 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.