Senior Data Engineer

About Us

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?

The role

As a Senior Data Engineersupporting the Risk and Operations Data Engineering team, you will design, build, and operate innovative data solutions within a fast-paced Agile environment. You'll play a key role in modernizing our data infrastructure and transforming our AWS‑centric data landscape, enabling advanced analytics, self‑service BI, and generative AI–driven insights.

You'll work closely with stakeholders in Risk, Finance, Legal, Regulatory, and other operational areas, turning business requirements into robust data products and platforms that support reporting, analytics, and data‑driven decision-making.

What you will do

Data Platform, Architecture & Engineering

• Design, develop, test, and support data-driven solutionsacross on‑prem and AWS environments.
• Build and maintain modern data lakehouse architectures(e.g., on AWS S3, Apache Iceberg or similar) and cloud data warehouses(e.g., Amazon Redshift).
• Develop robust ETL/ELT data pipelinesfor batch and streaming use cases, with a focus on performance, scalability, and reliability.
• Implement data modellingand transformation layers to support reporting, analytics, and self‑service use cases for Risk and Operations.
• Enhance platform integration by leveraging domain events and streaming technologiesto enable real‑time and near real‑time data processing.
• Ensure data solutions comply with security, privacy, and regulatory requirements relevant to Risk, Player Sustainability, Finance, Legal, and Regulatory areas.

Self-Service Analytics & Generative AI

• Collaborate with business stakeholders, analysts, and data scientists to enable self-service analyticsusing tools such as Power BIand Amazon QuickSight.
• Create sophisticated reporting and semantic models that deliver compelling narratives and actionable insights.
• Champion the adoption of generative AIfeatures (e.g., Cursor.ai, Amazon Q, Copilot, and similar tools) to enable intuitive, conversational analytics and accelerate data exploration.
• Design data products and views optimized for performance, usability, and accessibilityby non-technical users.

Engineering Excellence, Automation & CI/CD

• Improve data engineering processes through automationand standardization, implementing CI/CD pipelinesfor data pipelines, transformations, and infrastructure.
• Use and promote open-source data stack tools(e.g., dbt, Apache Airflow, Airbyte) for transformation, orchestration, and ingestion.
• Apply software engineering best practices (testing, code review, version control, observability) to data solutions.
• Conduct performance tuning and optimizationof queries, pipelines, and data stores to ensure efficient execution at scale.

Data Governance, Quality & Discovery

• Support and enhance data governance, discovery, and documentationusing platforms such as Open Metadataor similar tools.
• Ensure KPIs, metrics, and data documentationare accurate, complete, and up to date.
• Contribute to data quality frameworks(validation, testing, monitoring) and ensure adherence to compliance and regulatory standards.
• Define and track operational metricsand measurements for data products to ensure long‑term health and value.

Innovation, Collaboration & Operations

• Initiate and experiment with new ideas, tools, and approaches that support the Analytics & Insights (A&I)strategy and the evolution of our hybrid platform.
• Participate in proof-of-concept (POC) evaluationsof tools and technologies; synthesize and present findings to inform leadership decisions.
• Collaborate early and often on new data initiatives, working across architects and various technical teams to shape and deliver end‑to‑end solutions.
• Maintain and support data products in production, including release management, incident management, and on‑call support, focusing on optimal long‑term solutions.
• Build strong relationships with your team and stakeholders, working in an Agilemanner with transparent, proactive communication.

Your experience

Required

• 5+ yearsof experience in data engineering, with demonstrated ability to design and implement scalable, flexible modern data architectures.
• Strong hands-on experience with Oracle databases, including working with an Oracle on-premises data warehouse (data modelling, performance tuning, ETL/ELT, and operations) is mandatory; equivalent strong experience with SQL Server (T-SQL) in a comparable data warehouse environment will also be considered.
• Strong SQLskills, including writing and optimizing complex queries.
• Experience with ETL/ELTprocesses and data ingestion from diverse source systems.
• Proven experience building AWSdata pipelines and platforms (e.g., S3, Redshift) for data storage, computation, and security.
• Proven expertise with data transformation tools such as dbt.
• Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow) and, ideally, ingestion tools (e.g., Airbyte).
• Solid understanding of software development best practicesand CI/CDprocesses applied to data (testing, automation, deployment pipelines).
• Experience with performance tuning and optimizationof data pipelines and queries.
• Strong communication and stakeholder management skills, with the ability to translate business requirements into technical solutionsand influence decision-making across teams.

Advantageous

• Experience building data lakehousesolutions using technologies such as Apache Icebergor similar table formats.
• Hands-on experience with BI and visualization tools, such as Power BIand Amazon QuickSight, including semantic modelling and performance optimization.
• Experience with generative AIapplications in analytics and BI (e.g., Amazon Q, Copilot, or equivalent).
• Familiarity with data discovery and governance toolssuch as Open Metadata or similar catalog solutions.
• Experience working within regulated environments(e.g., finance, gaming, legal/regulatory) and knowledge of associated compliance requirements.

Our Way Of Working

Our world is hybrid.

A career is not a sprint. It’s a marathon. One of the perks of joining us is that we value you as a person first. Our hybrid world allows you to focus on your goals and responsibilities and lets you self-organise to improve your deliveries and get the work done in your own way.

Application Process

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.