Senior Data Platform Engineer (Python)

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 Platform Engineer (Python), you will take hands-on ownership of the data pipeline and ingestion layer that sits at the heart of our AWS data platform. You'll build, harden, and scale the pipelines that move and transform data across our ecosystem — making them faster, more reliable, and easier to extend as we onboard new sources and scale our ambitions. 

You'll work closely with Data Engineering, Architecture, and Security teams to raise the standard on how we build and ship data infrastructure — bringing engineering discipline, governance rigour, and a practical mindset to everything you touch. This is a consulting engagement with real ownership and influence — you won't be plugging gaps, you'll be shaping how we build. 

What You Will Do 

Data Pipeline Engineering 

• Design, build, and maintain scalable, secure Python data pipelines orchestrated with Apache Airflow, landing data cleanly into our AWS data lake (S3) and warehouse (Postgres/Redshift). 

• Own the ingestion and transformation layer — improving throughput, reducing latency, and making it straightforward to onboard new data sources without accruing technical debt. 

• Write clean, testable, well-documented Python that junior engineers can learn from and build on. 

Infrastructure, CI/CD & Deployments 

• Apply CI/CD best practices and Terraform (IaC) to make pipeline deployments repeatable, auditable, and consistent across environments. 

• Add meaningful monitoring and alerting so issues surface early and on-call isn't a guessing game. 

• Use Docker to containerise workloads and ensure portability across environments. 

Data Governance & Quality 

• Enforce data governance fundamentals: access control, schema validation, data quality checks, and GDPR compliance baked into the pipeline layer — not bolted on afterwards. 

• Define and maintain standards for how data is ingested, validated, and promoted through the platform. 

Lakehouse Transition 

• Actively contribute to our move toward a modern Lakehouse architecture — getting hands-on with Iceberg, Spark, Kafka, and dbt as we adopt them incrementally. 

• Bring a pragmatic view to tooling decisions — knowing when to adopt something new and when to keep it simple. 

Mentoring & Technical Collaboration 

• Mentor junior engineers through code reviews, pairing, and technical guidance — helping the team grow alongside the platform. 

• Input meaningfully on architecture and tooling decisions, bringing experience and considered opinions to the table. 

Your Experience 

Must Have 

• 5+ years building and operating production Python data pipelines at scale. 

• Hands-on AWS experience — S3, Redshift, Postgres, and the surrounding ecosystem. 

• Apache Airflow in production — DAG design, scheduling, backfill management, reliability. 

• Terraform, Docker, and CI/CD in real delivery environments, not just on paper. 

• Strong SQL and a solid grasp of data modelling principles. 

You'll Grow Into With Us 

• Spark, Apache Iceberg, Kafka, dbt — Lakehouse patterns and the tooling we're moving toward (exposure is a head start, not a requirement on day one). 

• Kubernetes for data workloads. 

• Observability tooling — Grafana or equivalent for pipeline monitoring and alerting. 

Bonus You Already Bring 

• Experience in online gambling, betting, or fintech — you understand the data volumes, the compliance pressure, and the pace. 

• ML or fraud detection background — familiarity with the data patterns and pipeline requirements that come with it. 

What We Offer 

• A consulting engagement with genuine ownership — you'll shape real platform decisions, not just execute tickets. 

• The chance to work on a data platform that's scaling fast, with a team that takes engineering quality seriously. 

• Exposure to a modern Lakehouse stack at an organisation moving quickly through that transition. 

• Competitive day rate and a collaborative, low-ego team to work alongside. 

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 model allows you to focus on your goals and responsibilities, and lets you self-organise to deliver your best work in the way that suits you. 

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 such as age, gender, origin, religion, sexual orientation, neurodiversity, or disability.