Data Engineer
Focusing on the Sportsbook product, this role involves building and evolving a next-generation data platform that powers trusted, scalable, and near real-time data assets across multiple brands and markets.
The successful candidate will work on a modern, event-driven lakehouse built on AWS, aligned to medallion architecture principles. They will contribute to the development of high-quality, well-governed data assets that support analytics, trading insight, and machine learning use cases.
This platform underpins critical decision-making across trading, risk, personalisation, and analytics, and plays a key role in scaling and standardising the data ecosystem.
- Build and maintain batch and streaming data pipelines, supporting ingestion, transformation, and serving layers.
- Develop and enhance data assets aligned to medallion architecture (bronze, silver, gold), ensuring quality and usability.
- Transform sportsbook domain data (bets, offers, rewards, digital data) into well-structured datasets for downstream consumption.
- Implement data transformation logic using modern tooling (e.g. dbt, Spark, SQL-based frameworks) with a focus on clarity and reliability.
- Contribute to streaming data pipelines (Kafka/Flink or equivalent) to support near real-time data use cases.
- Apply data quality checks and validation to ensure accuracy and consistency of data assets.
- Support the implementation of data contracts and schemas for reliable integration between systems.
- Monitor and troubleshoot pipelines to ensure performance, reliability, and cost efficiency on AWS.
- Collaborate with analytics, data science, and machine learning teams to deliver data solutions aligned to business needs.
- Contribute to data governance practices, including documentation, metadata, and dataset discoverability.
- 2–4 years experience in data engineering or a related field (required).
- Strong SQL skills and a good understanding of data modelling principles (required).
- Experience with data transformation tools (e.g. dbt, Spark) and workflow orchestration (e.g. Airflow or similar) (required).
- Familiarity with cloud-based data platforms, ideally AWS (required).
- Understanding of data pipeline design and ETL/ELT patterns (required).
- Exposure to streaming technologies (Kafka, Flink, or similar) (nice-to-have).
- Awareness of data quality, testing, and monitoring practices (required).
- Ability to work with stakeholders to understand requirements and deliver data solutions (required).
- Willingness to learn and grow in a fast-paced, evolving environment (required).
- Exposure to sports betting, trading, or financial data domains (nice-to-have).
- Familiarity with event-driven architectures (nice-to-have).
- Experience with semantic layers or BI tooling (nice-to-have).
- Exposure to data governance or metadata tooling (nice-to-have).
- Interest in supporting machine learning or analytics workflows (nice-to-have).
- Learning and development opportunities
- Social events and activities
- Inclusion networks
- Employee Assistance Programme
- Private medical insurance
- Long service awards
- Pension
FDJ United is one of Europe's largest gaming and betting groups, formed after French lottery operator La Française des Jeux (FDJ) acquired Kindred Group - the company behind Unibet - in 2024 and rebranded the enlarged group in 2025. Headquartered in Boulogne-Billancourt, France, it operates lottery, online sports betting, casino and poker across multiple European markets and Australia. Its portfolio includes well-known online brands such as Unibet, 32Red and Maria Casino, alongside FDJ's French lottery and retail network. The group is listed on the Euronext Paris exchange.