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 engineer to develop and maintain tools/products aimed at making the data science development work easier. The candidate will have evangelical mindset to identify, practice and promote better working methods in the fields of distributed computing to be used in data science engineering.

What we expect from you:

Preferrable 7-10 years of experience as Big data backend engineer

• Prior experience with scalable architecture and distributed processing.
• Strong Programming expertise in  SQL, Pyspark
• Expertise on major big data solutions like Spark,  Hive
• Experience in big data orchestrator like Airflow
• Strong programming skills in Python, with experience in FastAPI or any API framework
• Proficiency in unit testing and code quality assurance.
• Good hands-on experience on GIT or other code versioning tools
• Strong spark optimizations/tunning skills
• Experience on cloud-based data stores like Redshift and Big Query is an advantage.
• Experience in cloud solution architecture preferrable GCP and Azure.
• GitLab CI/CD is a plus.
• Excellent problem-solving and communication skills.
• Ability to work effectively in a collaborative team environment.

• Analyse complex data pipelines to identify performance bottlenecks, and suggest robust ways to optimize the workload in reasonable costs

• Work with the infra team to ensure robust, performant and scalable platform is available for data science development work
• Experience in re-engineering, automating and productionising code

Nice To Have

• Good experience on microservices architecture, docker and Kubernetes as orchestration.
• ML ops and ML experience using Spark
• Understanding of logging, monitoring, and alerting of production big data pipelines

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)