Data Lake Developer

We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages.

We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling and gaming. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our customers worldwide.

Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak.

Dive into expansive datasets and shape the future of data infrastructure as a Data Lake Developer.

The Data Engineering department builds and maintains the robust infrastructure that powers global operations. Handling vast amounts of information daily, the team ensures data is accessible, secure and optimised for complex analytical processing. As a Data Lake Developer, you will deliver everything from large-scale transformations linked to business-critical programmes to bespoke improvements for individual users.

Navigating a continually evolving technical landscape, you will collaborate with various teams to elevate the performance of the data lake and data warehouse. Tackling complex technical challenges, you will help satisfy the ever-changing demands of the business while maintaining exceptional standards of work.

This role is eligible for inclusion in the Company’s hybrid work from home policy.

Requirements

Commercial GCP background including BigQuery, Dataform and GCS; Knowledge of Data Lake technologies such as Airflow, Kafka, Flink and Python; Relational set-based processing through complex SQL queries; Proven ability to leverage AI within a production workflow; Background working within a Data Lake or Data Warehouse platform; Adaptability to thrive in a continually changing and reactive environment