Data Quality Engineer

Fdj United; Greater London; On-site; GBP 70,000 - 95,000; Full time

Job summary

FDJ UNITED is seeking a Data Quality Engineer to ensure reliability, accuracy, and trustworthiness of data across our next‑generation data platform supporting multiple brands and markets.

You’ll embed data quality, observability, and governance into the data ecosystem, enabling analytics, trading insight, and machine learning to run with confidence at scale.

Qualifications

• 3+ years experience in data engineering, data quality, or a related field.
• Strong SQL skills and experience working with large-scale datasets.
• Experience implementing data quality checks and validation frameworks (e.g. dbt tests, Soda, or similar).
• Familiarity with data pipeline orchestration and transformation tools (e.g. Airflow, Spark, dbt).
• Experience with cloud-based data platforms, ideally AWS.
• Understanding of data modelling and data lifecycle concepts.
• Experience with data observability, monitoring, and alerting practices.
• Ability to investigate and resolve data issues across distributed systems.

Responsibilities

• Design and implement scalable data quality frameworks across batch and streaming pipelines.
• Define and enforce data quality rules, including completeness, accuracy, consistency, timeliness, and validity.
• Use and enhance our existing data quality framework, partnering with engineering teams to implement robust data quality checks across development and production pipelines.
• Build automated data validation checks within ingestion and transformation pipelines (e.g. dbt tests, custom frameworks with Soda).
• Develop monitoring and observability capabilities to detect anomalies, data drift, and pipeline failures.
• Implement alerting mechanisms to surface data quality issues to relevant stakeholders in a timely manner.
• Partner with data engineers to embed quality controls within medallion layers (bronze, silver, gold).
• Define and maintain data contracts and schema validation to ensure reliability between producers and consumers.
• Perform root cause analysis of data issues and work with upstream and downstream teams to resolve them.
• Establish and track data quality SLAs/SLOs and report on data health metrics.
• Contribute to metadata management, including data lineage, definitions, and quality annotations.
• Support governance initiatives to improve data trust, discoverability, and standardisation across the platform.

Skills

SQL proficiency

Data quality checks

Data observability

Stakeholder collaboration

AWS experience

Data modelling

Problem solving

Quality governance

Tools

dbt

Soda

Airflow

Spark

Great Expectations

OpenMetadata

Hive Metastore

Job description

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?

About the Role

Focusing on our Sportsbook product, we’re looking for a Data Quality Engineer to help ensure the reliability, accuracy, and trustworthiness of data across our next-generation data platform, supporting 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 — embedding data quality, observability, and governance into the core of our data ecosystem. This role is critical in ensuring that data powering analytics, trading insight, and machine learning is consistent, well-understood, and fit for purpose.

Responsibilities

• Design and implement scalable data quality frameworks across batch and streaming pipelines.
• Define and enforce data quality rules, including completeness, accuracy, consistency, timeliness, and validity.
• Use and enhance our existing data quality framework, partnering with engineering teams to implement robust data quality checks across development and production pipelines.
• Build automated data validation checks within ingestion and transformation pipelines (e.g. dbt tests, custom frameworks with Soda).
• Develop monitoring and observability capabilities to detect anomalies, data drift, and pipeline failures.
• Implement alerting mechanisms to surface data quality issues to relevant stakeholders in a timely manner.
• Partner with data engineers to embed quality controls within medallion layers (bronze, silver, gold).
• Define and maintain data contracts and schema validation to ensure reliability between producers and consumers.
• Perform root cause analysis of data issues and work with upstream and downstream teams to resolve them.
• Establish and track data quality SLAs/SLOs and report on data health metrics.
• Contribute to metadata management, including data lineage, definitions, and quality annotations.
• Support governance initiatives to improve data trust, discoverability, and standardisation across the platform.

Qualifications

Your Experience

• 3+ years experience in data engineering, data quality, or a related field.
• Strong SQL skills and experience working with large-scale datasets.
• Experience implementing data quality checks and validation frameworks (e.g. dbt tests, Soda, or similar).
• Familiarity with data pipeline orchestration and transformation tools (e.g. Airflow, Spark, dbt).
• Experience with cloud-based data platforms, ideally AWS.
• Understanding of data modelling and data lifecycle concepts.
• Experience with data observability, monitoring, and alerting practices.
• Ability to investigate and resolve data issues across distributed systems.
• Strong attention to detail and a proactive approach to improving data reliability.
• Ability to collaborate with engineers, analysts, and business stakeholders.

Required Skills

• Experience in sports betting, trading, or financial data domains.
• Familiarity with streaming data quality challenges (e.g. late data, duplication, ordering).
• Experience with observability tools (e.g. Soda, Great Expectations, or similar).
• Exposure to metadata and governance tooling (e.g. OpenMetadata, Hive Metastore).
• Understanding of data contracts and schema evolution practices.
• Experience supporting machine learning or analytics data quality requirements.

Pay range and compensation package

Data quality is foundational to how we operate our sportsbook. This role ensures that the data powering trading decisions, analytics, and machine learning is accurate, reliable, and trusted. By embedding quality and observability into the platform, you’ll help reduce risk, improve decision-making, and enable teams across the business to confidently rely on data at scale.

Equal Opportunity Statement

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.