Senior Data Engineer

Derby
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Data Engineer – Up to £75k –  Derby (3 Days a Week) – SC Clearable – Infrastructure Projects

Are you a technically sharp, consultative data engineer ready to embed yourself in one of the UK’s most important infrastructure programmes?

We’re working with a global engineering consultancy at the forefront of the energy transition. They’re building out their data & analytics capability and this role is your chance to be the first data specialist on the project. 

The end client? One of the UK’s most recognisable engineering organisations. You’ll be the bridge between technical and business teams, delivering insights where spreadsheets currently dominate, and helping to modernise how critical infrastructure decisions are made.

What you’ll be doing:

Designing and building scalable, efficient datasets using SQL

Extracting, transforming, and consolidating segmented BIM data sources

Creating intuitive Power BI dashboards to support decision-making

Collaborating with engineers, BIM leads and project teams to define requirements and use cases

Acting as the go-to data expert in a hands-on, consultative capacity

Building trust on-site with stakeholders and laying the groundwork to productise insights in the long term

What they’re looking for:

Strong SQL skills (essential)

Cognos experience (must-have)

Power BI experience (must-have)

Python for data manipulation (preferred)

Comfortable working on-site in Derby 3 days a week

BIM knowledge or the ability to pick it up quickly

Someone who’s consultative, business-aware, and not afraid to get stuck in

Nice to have:

Azure or similar cloud platform experience

Understanding of BIM data standards (e.g. IFC, COBie, ISO 19650)

Experience working with sensitive or regulated data

Familiarity with engineering or asset-heavy environments

Why this role?

Up to £75k salary

SC clearance support (must be a sole UK national born in the UK)

Long-term opportunity to take ownership or even move into a bigger role

Join a growing capability in a global organisation backed by years of engineering heritage

This is a hands-on role in a company that’s serious about transforming how infrastructure projects use data, starting with you.

Interested?
Apply now or message me to find out more

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.