dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First.

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro.

We are looking for a talented Data Engineer To execute big data projects to create ready-to-use science products or software modules, engineering dunnhumby science into automated and scalable solutions available to capabilities teams. Developing the bog data back-end for science products and reusable science modules, ensuring they are productionised and available to the business and keeping in mind that developed solutions have to distil complex problems into compelling insights that resonate with clients. Working with senior data science engineers to conduct requirements analysis and design the solution. Input into reengineering and design based on own expertise and implement advice from colleagues to resolve challenge and create big data back-ends for highly performant Business Intelligence applications for desktop platforms.

What are we expecting from you 

• Bachelor’s degree or equivalent in an engineering/numerate subject e.g. Engineering, Stats, Math, Computer Science.
• Experience with and passion for building back-end workflows and applications using modern technologies, and an appetite for understanding and implementing data science algorithms.
• Would need to be a quick learner as some of the components of the tech stack could change
• Backend stack: Python, Pyspark, Postgres, SQL, GCP, Linux, Docker
• Strong programming skills in Python (including OOP)
• At least 2 years of back-end development using Pyspark, HDFS, Hive, any cloud platform.
• Good knowledge of SQL (joins, subqueries, etc.) and optimization techniques
• Knowledge of general software design, architecture and best practices
• Advanced English proficiency 

What you can expect from us

We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect.  Plus, thoughtful perks, like flexible working hours and your birthday off.

You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.

And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One and dh Thrive as the living proof.  We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. For an informal and confidential chat please contact stephanie.winson@dunnhumby.com to discuss how we can meet your needs. 

Our approach to Flexible Working

At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.

We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.

For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)