FDJ UNITED
Senior Cloud Data Engineer - KSP
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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?
Focusing on our Sportsbook product, we’re looking for a Senior Data Engineer to help build and evolve our next-generation data platform, powering trusted, scalable, and real-time data assets across multiple brands and markets.
You’ll primarily work on our Sportsbook Data Platform — a modern, event-driven lakehouse built on AWS and aligned to medallion architecture principles — delivering high-quality, well-governed data products that support analytics, trading insight, and machine learning use cases. This platform underpins critical decision-making across trading, risk, personalisation, and analytics, and represents a key step forward in standardising and scaling our data ecosystem.
What You’ll Do
- Design and build scalable batch and streaming data pipelines, supporting ingestion, transformation, and serving layers.
- Develop and maintain data assets aligned to medallion architecture (bronze, silver, gold), ensuring clear ownership, quality, and usability.
- Model sportsbook domain data (bets, offers, rewards, digital data) into reusable, well-defined datasets for downstream consumption.
- Implement data transformation logic using modern tooling (e.g. dbt, Spark, SQL-based frameworks), ensuring consistency and testability.
- Build and optimise streaming data pipelines (Kafka/Flink or equivalent) to enable near real-time data availability.
- Ensure data quality and reliability through validation frameworks, observability, and robust handling of late-arriving or inconsistent data.
- Design data contracts and schemas that enable reliable integration between upstream event producers and downstream consumers.
- Optimise pipelines and storage for performance and cost efficiency within AWS.
- Collaborate with analytics, data science, and machine learning teams to translate business requirements into high-quality data assets.
- Contribute to data governance practices, including metadata management, lineage, and discoverability.
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What You’ll Work On
- A modern sportsbook data platform built on AWS, supporting both real-time and batch data processing.
- Medallion-aligned data layers enabling progressive refinement from raw ingestion through to curated, business-ready datasets.
- Streaming pipelines that ingest and process high-volume sportsbook events (bets, pricing, settlements).
- Curated data assets powering trading analytics, risk monitoring, and customer personalisation models.
- Integration with semantic layers, BI tools, and machine learning platforms.
- Data governance and metadata tooling to improve transparency, trust, and reuse across the organisation.
Your Experience
- 5+ years experience in data engineering, building and maintaining scalable data platforms.
- Strong SQL and data modelling skills, with experience designing analytical datasets.
- Experience with modern data stack tools (e.g. dbt, Spark, Airflow, or similar orchestration and transformation frameworks).
- Experience with cloud-based data platforms, ideally AWS.
- Understanding of medallion architecture or similar data layering approaches.
- Experience working with streaming technologies (Kafka, Flink, or similar).
- Strong understanding of data quality, testing, and observability practices.
- Experience designing schemas and handling data consistency challenges in distributed systems.
- Ability to work closely with stakeholders to translate business needs into scalable data solutions.
- Proactive mindset with the ability to operate in evolving environments and iterate on solutions.
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Nice to Have
- Experience in sports betting, trading, or financial data domains.
- Familiarity with event-driven architectures and real-time data products.
- Experience with semantic layers (e.g. Cube.js) or metrics-layer design.
- Exposure to data governance and metadata tools (e.g. OpenMetadata, Hive Metastore).
- Experience supporting machine learning workflows and feature engineering pipelines.
Why This Role Matters
This platform is central to how we enable trusted, scalable, and reusable data across sportsbook. It provides the foundation for analytics, trading insight, and machine learning, enabling better and faster decision-making across the business. From a technology perspective, it establishes a governed, extensible data architecture that can evolve with increasing data volume, complexity, and real-time demands.
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.
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