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?
Senior Data Engineer — A hands-on engineering role building and optimising scalable ETL/ELT pipelines and Lakehouse architectures across a modern multi-cloud platform using Python, Spark, Airflow, and dbt.
Requires 5+ years of data engineering experience with strong expertise in SQL, CI/CD, data quality frameworks, and cloud technologies (S3, Athena, Redshift), with a plus for streaming and AI tooling experience.
Overview
A Senior Data Engineer position within an agile team, focused on building scalable data pipelines and modernizing a multi-cloud data platform. The role involves working with streaming technologies, Lakehouse architectures, and leveraging automation/AI to improve efficiency.
Key Responsibilities- Pipeline Development: Build ETL/ELT pipelines (Python, SQL), optimize Spark/PySpark jobs, manage Airflow DAGs, and implement dbt transformations.
- Lakehouse Architecture: Design medallion-style architectures using S3 and modern table formats (Iceberg, Delta Lake) with optimized layouts.
- Platform Infrastructure: Create reusable frameworks, enforce data contracts, build CI/CD pipelines, and establish observability practices.
- Data Quality: Implement validation frameworks, data contracts, and SLIs/SLOs for critical pipelines.
- 5+ years in data engineering
- Strong Python, advanced SQL, Airflow, Spark/PySpark, dbt, and CI/CD proficiency
- Experience with Lakehouse architectures, dimensional modeling, and cloud data warehouses (S3, Athena, Redshift)
- Data quality frameworks, monitoring, and schema evolution expertise
- Streaming platforms (Kafka, Kinesis)
- AI coding assistants (Cursor, Claude Code, Copilot)
- Terraform, Kubernetes/Docker
- Data catalog/metadata management experience
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.
