Developer with Data Engineering focus

NG Bailey
Leeds
3 weeks ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Developer

Senior Staff Data Engineer

SAS Data Engineer

SAS Data Engineer

Data Engineer

Data Scientist

Developer

Leeds – Hybrid  

Permanent  

Summary  

We’re currently seeking a multi-skilled developer to join our ICT team here in Leeds. Reporting directly to our ICT Development Lead, you’ll focus initially on Microsoft Fabric Data Engineering.  In this role, an ideal candidate will have a strong background in software development and will have demonstrated experience with one of the Azure Data Analytics platforms e.g. Fabric, Synapse or ADF. 

Some of the key deliverables for the role will include: 

  • Designing, developing and maintaining data pipelines within Microsoft Fabric, including Lakehouse, Data Engineering and Data Warehouse components 
  • Building scalable ETL/ELT workloads using Spark notebooks and Python, following data engineering best practices, including a meta driven framework. 
  • Applying data modelling and data warehousing principles to support business intelligence and analytics solutions 
  • Working alone and with others on new business systems and/or modify existing systems to specific user/system interfaces 
  • Awareness of the software engineering life cycle for development and the concepts and practices required to implement effective information systems. 
  • IT setups in liaison with colleagues and users as appropriate including: 
  • Analysis and modelling of user requirements, specifying information flows, processes and procedures 
  • Converting specifications into detailed designs taking account of technical and non-technical features and limitations of the target implementation environment. 
  • Translating design requirements and implementing into physical database structures 
  • Constructing or modifying, testing and correcting program modules from detailed specifications 
  • Interpreting and executing defined test plans 
  • Installing fully tested software in target environments 
  • Producing documentation of all work in accordance with agreed standards 
  • Taking part in client/user meetings (both formal and informal) and assist in presenting issues and solutions both orally and in writing 
  • Participating in technical discussions with our third parties 
  • Undertaking general business systems support on internal/third party systems and adopt a flexible and consistent approach to offering on-site support to users.

What we’re looking for:  

  • Proven experience in Microsoft Fabric or similar technologies 
  • Solid knowledge in Python & Spark Notebooks, Azure Data Factory / Azure 
  • Demonstrable experience in Data Warehousing / Data Marts  
  • Previously used one or more of: 
    • SQL 
    • Oracle SQL 
    • T-SQL  
    • PLSQL 
  • Previously used one or more of:  
    • Power BI 
    • Crystal 
    • SQL Server Reporting Services (SSRS)  
  • Synapse Azure Integration Services  
    • Azure API Management, 
    • Azure Logic Apps 
    • Azure Functions 
    • Azure Service Bus 
  • Demonstrable experience with traditional programming languages and/or low-code development tools  
  • Experience with Source Control 

What would be desirable  

  • Microsoft Power Platform  
  • Azure DevOps  
  • HTML/CSS  
  • Further knowledge or experience with ERP, WMS,  
  • .NET Technologies  

Next Steps: 

As a business, we’re on a journey to build on our culture where everyone is included, treated fairly and with respect. This starts with recruitment and how we bring people into the organisation.  

We’ll do our best to outline the recruitment process to you ahead of time with plenty of notice. If you require any accommodations to participate in the application or interview process, please let us know and we will work with you to ensure your needs are met. 

About Us: 

We are one of the leading independent engineering and services businesses in the UK. Founded in 1921, with a turnover of £500m and 3000 employees, we are proud of our history of developing great people through our investment in training. 

Working across a variety of sectors within the building and infrastructure industry, our innovative, responsible and forward-thinking approach allows us to work on fantastic ground-breaking projects, providing solutions using the latest tools and technologies. 

Progression is something we value, and we will make sure that when you join us you have a clearly defined development path, supported by regular reviews, training and ongoing support to enable you to be the best you can be. #LI-LP1#LI-hybrid

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 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.

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.

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.