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.
What you will do
- 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.
What You Bring
- 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.
Your experience
- Experience with other reporting/BI tools such as Power BI or AWS QuickSight.
- Experience with cloud data warehouses like AWS Redshift, Snowflake, or BigQuery.
- 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).
