Senior Machine Learning DataOps Engineer

About Us

At FDJ UNITED, we don't just follow the game, we reinvent it.

FDJ UNITED is one of Europe’s leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you’ll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day.

We’re looking for bold people who are eager to succeed and ready to level-up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field.

Join us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME?

The role

Focussing on our Sportsbook product, our ML DataOps will play a critical role in streamlining and optimising data management processes, ensuring faster, more reliable, and data-driven decision-making. Given the dynamic nature of the industry, leveraging real-time insights, maintaining data integrity, and enhancing operational efficiency are essential for delivering a seamless customer experience while ensuring regulatory compliance

We are now at the next stage of our journey, building our capability for developing end-to-end machine learning data products, from research conducted by our Data Scientists through to production applications built by our Machine Learning Engineers. Our ML DataOps will align with cross-functional product teams and contribute to the development of high-quality Sportsbook data products. We are currently focusing on areas including personalisation and relevancy, and customer risk management.

Additionally, we are building the core toolset and capability required for our product and data engineering teams to scale efficiently and iterate rapidly. This includes developing a Data Lakehouse for use in both research and production contexts, and building the tooling we need to build, monitor and test our data products.

Your experience

We think that to be successful in this role you will be able to demonstrate many of the following attributes:

• 3-5 years relevant commercial experience.
• Excellent Java skills.
• Experience working alongside Data Engineers and ML Engineers.
• Experience with version control systems and CI/CD pipelines.
• Infrastructure as Code experience (Terraform or CloudFormation).
• Experience using Spark.
• Experience using Kafka (including Kafka Streams).
• Data Engineering experience.
• Understanding of the machine learning model lifecycle and operations (MLOps).
• Experience in cloud computing, ideally AWS.
• Passionate about your personal development.
• Excellent interpersonal skills: able to collaborate, explain complex topics and contribute to the success of cross-functional DE/MLE product teams.
• Ability to deal with and account for uncertainty, with the flexibility to learn by iteration. Proactive.

In addition, it would be an advantage if you also have:

• A knowledge of enterprise data concepts, including Data Mesh.
• AWS certification.
• An interest in mentoring and coaching more junior team members.

Our Way Of Working

Our world is hybrid.

A career is not a sprint. It’s a marathon. One of the perks of joining us is that we value you as a person first. Our hybrid world allows you to focus on your goals and responsibilities and lets you self-organise to improve your deliveries and get the work done in your own way.

Application Process

We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.