Data Engineer

dunnhumby is the global leader in Customer Data Science partnering with the worlds 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 2500 experts in offices throughout Europe Asia Africa and the Americas working for transformative iconic brands such as Tesco Coca-Cola Nestlé Unileverand Metro.

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.

Job Title: Data Engineer

Job Summary

We are seeking a talented and self-driven Data Engineer to design develop and optimize real-time and batch data pipelines that power our retail media measurement 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 practicesbuilding 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 2 years of expertise in data engineering with a proven track record of designing and optimizing scalable solutions.
  Strong experience with cloud data warehouses and query engines
• Experience with data cataloging metadata management and lineage tools
• Experience with data quality tooling will be a plus.
• Technical Expertise:
• Strong expertise in big data technologies such as SQL PySpark and Hive
• Experience with big data workflow orchestrators like Argo Workflows
• Hands-on experience with cloud-based data stores likeRedshiftorBigQuery(preferred).
• Familiarity with cloud platforms preferablyGCPorAzure.
• Development Practices:
• Strong programming skills inPython with experience in frameworks likeFastAPIor similar API frameworks.
• Proficiency in unit testing and ensuring code quality.
• Hands-on experience with version control tools likeGit.
• 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 usingDocker and orchestration tools likeKubernetes.

• Working knowledge ofmachine learning workflows with feature engineering model training deployment and monitoring etc.

• Understanding of logging monitoring and alerting for production-grade big data pipelines.
• 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 wont just meet your expectations. Well defy them. So youll enjoy the comprehensive rewards package youd 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.

Youll 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 dont 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.

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