Senior Engineer

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. 

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, Nestlé, Unilever and Metro.

 

Dunnhumby helps retailers and brands deliver better experiences through Customer First strategies.

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.Retail Media is transforming how advertisers connect with consumers through personalized and targeted campaigns across retailers' digital and physical touchpoints. Retail Media Measurement plays a pivotal role in ensuring the effectiveness of these campaigns, driving value for advertisers, retailers, and consumers alike.

This role focuses on designing, building, and scaling solutions that enable the accurate measurement of retail media campaigns across various channels. By providing actionable insights, it empowers stakeholders to optimize media investments, improve ROI, and enhance the overall customer experience.

We are seeking a talented and self-driven Senior Data Engineer to design, develop, and optimize real-time and batch data pipelines that power our retail media measurement solutions. In this role, you will work with Python, Apache Spark, and modern streaming frameworks to process and analyze data, enabling near-real-time decision-making for critical business applications in the retail media space.

Beyond traditional data engineering, you will also contribute to MLOps practices—building scalable infrastructure to support machine learning workflows, automating model deployment, monitoring performance, and ensuring reproducibility across environments. Your work will help bridge the gap between data engineering and machine learning, enabling seamless integration of predictive models into production pipelines.

You will collaborate closely with Data Scientists, Analysts, Lead Engineers, and Product Managers to deliver robust, efficient, and production-ready data solutions. As a Senior Data Engineer, you will focus on designing scalable pipelines, mentoring junior engineers, and championing best practices in data engineering and MLOps.

Your contributions will ensure the reliability, scalability, and performance of our data and ML infrastructure, driving actionable insights and measurable impact for the business. This role offers an excellent opportunity to deepen your expertise in modern data engineering and MLOps practices while working with cutting-edge technologies in a fast-evolving industry.

What We Expect from you:

• Experience:
• Bringing 7–9 years of expertise in data engineering, with a proven track record of designing and optimizing scalable solutions.
• Technical Expertise:
• Strong expertise in big data technologies such as SQL, Pyspark and Hive
• Experience with any workflow orchestrators like Argo Workflows, Airflow
• Hands-on experience with cloud-based data stores like Redshift or Bigquery (preferred).
• Proficiency in any cloud platforms, preferably GCP or Azure.
• Development Practices:
• Strong programming skills in Python, with experience in frameworks like FastAPI or similar API frameworks.
• Proficiency in unit testing and ensuring code quality.
• Hands-on experience with version control tools like Git.
• Hands-on experience ensuring reliability of production-grade big data pipelines through robust logging, monitoring, and alerting.
• Optimization & Problem Solving:
• Ability to analyze complex data pipelines, identify performance bottlenecks, and suggest optimization strategies.
• Work collaboratively with infrastructure teams to ensure a robust and scalable platform for data science workflows.
• Collaboration & Communication:
• Excellent problem-solving skills and the ability to work effectively in a team environment.
• Proven mentoring and communication skills, fostering collaboration across teams and effectively sharing technical expertise.

Nice To Have:

• Experience with microservices architecture, containerization using Docker, and orchestration tools like Kubernetes.
• Exposure to MLOps practices or machine learning workflows using Spark.

• Working knowledge of machine learning workflows with feature engineering, model training, deployment, and monitoring etc.

• Good working knowledge with NoSQL databases such as MongoDB, Cassandra, or DynamoDB.

This role is ideal for someone eager to grow their expertise in modern data engineering practices while contributing to impactful projects in a collaborative environment.

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, dh Enabled 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. 

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)