Junior ML DataOps Engineer

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?

About the role

FDJ United’s ambition is to be the most insight-driven gambling company, and in recent years we’ve invested heavily in our data capabilities. Focusing on our Sportsbook product, DataOps plays a critical role in streamlining and optimising data management processes, ensuring faster, more reliable and data-driven decision-making. In a dynamic and highly regulated industry, leveraging real-time insights, maintaining data integrity and enhancing operational efficiency are essential to delivering a seamless customer experience.

As a Junior ML DataOps Engineer, you will help us build, operate and improve the tools, infrastructure and workflows that enable our Data Scientists, Data Engineers and Machine Learning Engineers to deliver high-quality data and ML products at scale. You will contribute to automating processes, improving data quality, developing testing and monitoring capabilities, and making our development and deployment workflows more reliable and efficient.

You will also help us explore and adopt new technologies, including Generative AI, to improve how we build, test and operate our data products. This includes contributing to our Data Lakehouse capabilities and developing tooling that helps our teams work more efficiently, experiment safely and move solutions into production with confidence.

Working alongside experienced engineers, you will have the opportunity to develop your skills across software engineering, data engineering, cloud infrastructure and AI operations. We are looking for someone with a strong technical foundation, a genuine interest in AI and automation, and the curiosity and initiative to learn, experiment and grow as part of a collaborative engineering team.

About you

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

• Good programming skills in Python or Java, with a willingness to develop further.
• An understanding of software engineering fundamentals, including version control, code reviews, testing and maintainable code.
• An interest in DataOps, DevOps, MLOps or ML Engineering, and how these disciplines help teams deliver reliable production systems.
• Familiarity with CI/CD pipelines and automated software deployment, or a willingness to learn.
• An understanding of data pipelines, data processing and the importance of data quality and reliability.
• An interest in AI and machine learning, including Generative AI and the operational challenges of taking AI solutions into production.
• Familiarity with cloud computing, ideally AWS, or experience with cloud-based projects.
• A proactive approach to problem-solving, with the ability to investigate issues, learn from feedback and develop practical solutions.
• Good communication and interpersonal skills, with the ability to collaborate with engineers and other stakeholders across different disciplines.
• A growth mindset, with enthusiasm for learning new technologies and developing your technical capabilities.
• The ability to work with uncertainty, adapt to changing priorities and approach unfamiliar problems with curiosity and initiative.

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

• Experience with Python-based data processing or automation.
• Familiarity with AI/ML frameworks, APIs or Generative AI tools.
• Exposure to Spark, Kafka or other distributed data processing technologies.
• Experience with Docker, containers or Kubernetes.
• Familiarity with infrastructure as code, such as Terraform or CloudFormation.
• Exposure to AWS services and cloud-native application development.
• An understanding of automated testing, data quality checks, monitoring, logging or alerting.
• Experience with Git-based workflows and tools such as GitLab.
• An interest in data platforms, Data Lakehouse architectures or enterprise data concepts.
• Personal projects, academic work or contributions that demonstrate curiosity and practical experience in software engineering, data or AI.

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.