Data Engineering Specialist

Ansty, Warwickshire
2 days ago
Create job alert

Cadent Gas Ltd

Shape the future of Data at Cadent  

We’re looking for a Data Engineering Specialist to help us deliver on our ambition to become a truly data-driven business. This is more than a technical role – it’s your opportunity to shape how we capture, connect, and use data across one of the UK’s most vital utility networks.

At Cadent, we’re not just moving gas. We’re enabling the future of energy – safely, sustainably, and intelligently. That journey starts with data. From regulatory reporting to real-time operational insights, the way we manage, model and move data has a direct impact on our people, our performance, and our customers.

As a Data Engineering Specialist, you’ll be at the core of our growing Data team within the Chief Information Office (CIO). Working in high-performing teams, you’ll build high-quality, enterprise-level data models and pipelines using SAP Datasphere, Databricks, and other cutting-edge tools. Your work will underpin analytics, dashboards, and innovations in AI and machine learning and ultimately help us make better decisions, faster.

We’re building something powerful. Come and help us make it real.

Why you'll love this job:  

We’re transforming how we think about and use data, and you’ll be part of the engine room. This is your chance to work with modern tools in a cloud-first, agile environment, develop your skills alongside experienced engineers and architects, create real business impact through smarter data design, be part of a positive, inclusive, forward-thinking culture, and help drive the energy transition for the UK.

Model & design - Build reusable, enterprise-level data models using SAP Datasphere
Code & create - Develop complex SQL and ABAP CDS views for analytics and reporting
Transform & optimise - Use PySpark and Databricks to manipulate big data efficiently
Automate & schedule - Manage workflows, jobs and clusters for scalable data processing
Collaborate & deliver - Engage across agile teams to build high-impact solutions  

What you'll bring: You’re curious, collaborative, and deeply technical. You love solving complex problems and transforming raw data into structured insights.

Experience in building data pipelines and models in SAP Datasphere or SAP BW4/Hana  
Advanced skills  in SQL, data modelling, and data transformation  
Familiarity with Databricks, Apache Spark, PySpark, and Delta Lake  
Agile mindset with experience in DevOps and iterative delivery  
Excellent communication and stakeholder engagement abilities    

Sound like a fit? Let’s build the future of data at Cadent – together

Related Jobs

View all jobs

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

Data Engineering Product Owner, Technology, Data Bricks, Microsoft

Data Engineering Product Owner, Technology, Data Bricks, Microsoft

Senior Data Engineering Consultant

Senior Data Engineering Consultant

Data Engineer

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.