Data Engineer

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.

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.

Exposure to sports betting, trading, or financial data domains.

Familiarity with event-driven architectures.

Experience with semantic layers or BI tooling.