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FDJ UNITED

Data Engineer

London
Posted about 3 hours ago
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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?

Focusing on our Sportsbook product, we’re looking for a Data Engineer to help build and evolve our next-generation data platform, powering trusted, scalable, and near real-time data assets across multiple brands and markets.

You’ll work on our Sportsbook Data Platform — a modern, event-driven lakehouse built on AWS and aligned to medallion architecture principles — contributing 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 our data ecosystem.

What You’ll Do

  • 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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

What You’ll Work On

  • A modern sportsbook data platform built on AWS, supporting both real-time and batch data processing.
  • Medallion-aligned data layers transforming raw data into curated, business-ready datasets.
  • Data pipelines processing sportsbook events such as bets, pricing, and settlements.
  • Data assets supporting trading analytics, risk monitoring, and customer personalisation.
  • Integration with BI tools, semantic layers, and machine learning platforms.
  • Data governance and metadata tooling to improve transparency and trust in data.

Your Experience

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  • 2–4 years experience in data engineering or a related field.
  • Strong SQL skills and a good understanding of data modelling principles.
  • Experience with data transformation tools (e.g. dbt, Spark) and workflow orchestration (e.g. Airflow or similar).
  • Familiarity with cloud-based data platforms, ideally AWS.
  • Understanding of data pipeline design and ETL/ELT patterns.
  • Exposure to streaming technologies (Kafka, Flink, or similar) is beneficial.
  • Awareness of data quality, testing, and monitoring practices.
  • Ability to work with stakeholders to understand requirements and deliver data solutions.
  • Willingness to learn and grow in a fast-paced, evolving environment.

Nice to Have

  • Exposure to sports betting, trading, or financial data domains.
  • Familiarity with event-driven architectures.
  • Experience with semantic layers or BI tooling.
  • Exposure to data governance or metadata tooling.
  • Interest in supporting machine learning or analytics workflows.

Why This Role Matters

This role contributes to building the trusted data foundation that powers analytics, trading insight, and machine learning across sportsbook. By delivering reliable and well-structured data assets, you’ll help enable better decision-making and support the continued evolution of our scalable, modern data platform.

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.

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Skills

Data Engineering
SQL
AWS
Dbt
Spark
Data Modeling
ETL
ELT
Kafka
Flink
Data Pipelines
Medallion Architecture
Data Governance
Streaming Data
Cloud Platforms

Location

London, England, United Kingdom

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