Data Engineer

AkzoNobel
Altrincham
1 week ago
Create job alert

Since 1792, we’ve been supplying the innovative paints and coatings that help to color people’s lives and protect what matters most. Our world class portfolio of brands – including Dulux, International, Sikkens and Interpon – is trusted by customers around the globe. We’re active in more than 150 countries and use our expertise to sustain and enhance the fabric of everyday life. Because we believe every surface is an opportunity. It’s what you’d expect from a pioneering and long-established paints company that’s dedicated to providing sustainable solutions and preserving the best of what we have today – while creating an even better tomorrow. Let’s paint the future together.


Competitive salary plus market leading benefits package


We’re looking for a Data Engineer to play a pivotal role in transforming data into meaningful insight that drives smarter decision-making across the business. In this role, you’ll work closely with stakeholders to design, build, and deliver data solutions that help teams optimise performance and achieve their objectives.


At AkzoNobel, we’re proud of our heritage and our commitment to innovation and continuous improvement. You’ll join a collaborative, forward-thinking environment where data is central to how we operate and where your expertise will have a tangible impact.


What you’ll do:

  • Collect, clean, and manage data from multiple sources to ensure accuracy, consistency, and reliability.
  • Analyse large datasets to identify trends, patterns, and opportunities that support business decision-making.
  • Build and maintain dashboards, reports, and visualisations that translate complex data into clear insight.
  • Develop and test algorithms, models, and machine learning solutions to address complex business challenges.
  • Work closely with business stakeholders and IT teams to understand requirements and embed data-driven insight into strategy.
  • Present findings and recommendations clearly to both technical and non-technical audiences.
  • Support data governance, privacy, and security standards across all reporting and analytics activity.
  • Continuously improve data pipelines, reporting capabilities, and analytical approaches as business needs evolve.

What you bring:

  • Strong experience working with data analysis and visualisation tools such as Excel, SQL, Power BI, and Visual Studio.
  • A solid understanding of statistical analysis, modelling, and machine learning techniques.
  • Experience working with databases and data management technologies.
  • Strong problem-solving skills with the ability to turn data into actionable insight.
  • Excellent communication skills, able to explain complex concepts clearly and confidently.
  • Strong attention to detail and a commitment to data accuracy and quality.
  • Ability to adapt and thrive in a fast-paced, evolving environment.

Who you are:

  • Curious, analytical, and driven by uncovering insight from data.
  • Confident working independently while collaborating closely with stakeholders.
  • Comfortable managing ambiguity and translating unclear requirements into structured solutions.
  • Proactive, organised, and motivated to continuously improve how data is used across the business.

Ready to turn data into insight that drives real business impact?


Apply now and help shape data-driven decision-making at AkzoNobel.


At AkzoNobel we are highly committed to ensuring an inclusive and respectful workplace where all employees can be their best self. We strive to embrace diversity in a context of tolerance. Our talent acquisition process plays an integral part in this journey, as setting the foundations for a diverse environment. For this reason we train and educate on the implications of our Unconscious Bias in order for our TA and hiring managers to be mindful of them and take corrective actions when applicable. In our organization, all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age or disability.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

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

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

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

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.

Data Engineering Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data engineering in your 30s, 40s or 50s? You’re not alone. In the UK, companies of all sizes — from fintechs to government agencies, retailers to healthcare providers — are building data teams to turn vast amounts of information into insight and value. That means demand for data engineering talent remains strong, but there’s a gap between media hype and the real pathways available to mid-career professionals. This guide gives you the straight UK reality check: which data engineering roles are genuinely open to career switchers, what skills employers actually look for, how long retraining really takes and how to position your experience for success.