Data Engineer

FDJ is on the lookout for a talented Data Engineer to help us become one of the leading data-driven gambling companies. In this dynamic position within our Data Department, you’ll collaborate with diverse stakeholders to maximize data utility, enabling insightful reporting and data-driven decision‑making.

• Build and run data pipelines that ingest data from sources like Oracle databases, APIs, and SFTP files into our Oracle data warehouse.
• Write and maintain SQL and PL/SQL (Oracle 19c+) for data processing, reporting, and analytics.
• Help design and maintain data models (3NF, Star, Snowflake) that support reporting and downstream applications.
• Develop and maintain dashboards and reports using tools like Power BI.
• Investigate data issues, perform root‑cause analysis, and help resolve data and reporting problems for stakeholders.
• Collaborate with stakeholders to understand their data and reporting needs and help turn them into practical data solutions.
• Help support our data platforms, including participating in on‑call and incident handling on a rotation.
• Work in an Agile team, contributing to planning, delivery, and continuous improvement.

• Solid experience working with Oracle databases (19c+), using SQL and PL/SQL in production.
• 5+ years working with large datasets in a data engineering or similar role.
• Good understanding of data warehousing concepts, data modelling (Star/Snowflake/3NF), and ETL/ELT pipelines.
• Experience tuning SQL/PLSQL queries and improving performance of reports and data extracts.
• Hands‑on experience with at least one cloud data platform, ideally AWS (e.g. Redshift, RDS, or similar).
• Exposure to modern data transformation tools such as dbt or similar frameworks.
• Basic understanding of cloud concepts (networking, storage, security) and CI/CD for data pipelines.
• An interest in learning new tools and technologies, and in improving data quality, reliability, and performance.

• Experience with other reporting/BI tools such as Power BI or AWS Quick Sight.
• Experience with cloud data warehouses like AWS Redshift, Snowflake, or Big Query.
• Some knowledge of Kafka and a programming language (e.g. Python or Java) for building data workflows and automation.
• Familiarity with AWS services such as S3, Glue, Lambda, EMR, or streaming tools like MSK/Kinesis.
• Experience with basic data governance, data quality checks, and security practices (e.g. RBAC, encryption, handling PII).