FDJ UNITED Logo

FDJ UNITED

Data Engineer

Posted 7 Hours Ago
Be an Early Applicant
In-Office
London, Greater London, England, GBR
Mid level
In-Office
London, Greater London, England, GBR
Mid level
Build and maintain batch and streaming data pipelines for a modern AWS sportsbook data platform. Develop medallion-aligned datasets using SQL, dbt, Spark, and related tools; support Kafka or Flink streaming; implement data quality checks, schemas, monitoring, and governance; and troubleshoot pipeline performance and costs. Collaborate with analytics, data science, machine learning, trading, risk, and personalization teams to deliver reliable, scalable data assets.
The summary above was generated by AI

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.

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

Similar Jobs

27 Days Ago
Easy Apply
Hybrid
London, England, GBR
Easy Apply
Senior level
Senior level
Artificial Intelligence • Machine Learning • Software
Design, build, deploy, and optimize distributed big-data ingestion, standardization, and ML pipelines at scale. Support platform reliability, cost controls, security accreditations, and customer integrations. Serve as technical lead in client meetings, mentor engineers, and recommend tools and best practices for data pipeline development and deployment.
Top Skills: AWSAzureDatabricksDatadogDockerEc2GCPGitIamKubernetesOpensearchPostgresPythonRest ApisS3SparkSQLTerraform
5 Days Ago
Hybrid
London, Greater London, England, GBR
Mid level
Mid level
Fintech • Mobile • Payments • Software • Financial Services
Own and operate production Python infrastructure for FX pricing, risk, and trading systems. Responsibilities include developing microservices, shared quantitative libraries, monitoring and alerting, CI/CD, deployment, incident response, and root-cause analysis. The role also offers growth into curve construction, pricing models, trading strategies, risk modeling, backtesting, and customer behavior modeling while collaborating with quants, traders, analysts, product managers, and engineers.
Top Skills: Ci/CdDatabasesFlinkIcebergKafkaMicroservicesPythonRedisSnowflakeSpark
5 Hours Ago
In-Office
Tower Hill, London, Greater London, England, GBR
Mid level
Mid level
Fintech • Payments • Financial Services
Design and maintain enterprise ETL/ELT pipelines, data models, and scalable cloud data platform solutions using Azure Data Factory, Synapse, and Databricks. Develop complex SQL and Python transformations, implement CI/CD, support data reliability and SLA obligations, and oversee testing, code promotion, documentation, and platform improvements. The role also supports migration from SQL Server data warehouses and provides end-of-life support for SAP Data Services.
Top Skills: Azure Data FactoryAzure DatabricksAzure Synapse AnalyticsCi/CdDatabricksDelta LakehouseEltETLPythonRestful ApisSap Data ServicesSparkSQLSQL Server

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account