Lead Data Engineer (Audience Intelligence)

Lead Data Engineer (Azure / Databricks / Python)

Who we are

We are Two Circles. We are a Sports & Entertainment Marketing business. We grow audiences and revenues. We do that by knowing fans best. We work with clients to help them understand & influence what their fans are doing – the way fans spend their money, the events that fans attend, the channels fans respond to, the content fans watch and more. And we use the understanding this gives us to help our clients grow. Grow their audiences and grow their revenues - both direct to consumer and business to business revenues. Our platforms and services are trusted by over 900 clients globally, including the English Premier League, Red Bull, UEFA, VISA, the NFL, Nike and Amazon. We are almost 1000 people, based out of 14 offices, and we deliver work for sports and entertainment businesses of all shapes and sizes all over the world.

What you will do

We're looking for a talented Data Engineer to join our squad of >100 Data & BI Engineers, working on our Audience Intelligence Platform. You will be helping to build the leading data management and analytics platform for the sports industry. In this role, you'll work with cutting-edge technologies to design, build, and optimize scalable data solutions, enabling teams, leagues, and organizations to unlock the full potential of their data. If you're passionate about data engineering, enjoy collaborating in a fast-paced environment, and want to make an impact in the sports industry, we’d love to hear from you!

Your role will be varied and evolve as quickly as you can learn and develop. Your initial duties will involve:

• Design, build, and test scalable data platform solutions in Azure, leveraging tools like ADF, Databricks, and Function Apps, using Python.
• Develop high-quality data products, ensuring efficiency, reliability, and performance across our data pipelines.
• Collaborate closely with product and marketing teams to deliver data-driven insights and solutions that provide high business value.
• Write clean, maintainable code following best practices and development frameworks, ensuring robust data engineering standards.
• Continuously improve and optimize data workflows, monitoring performance and implementing enhancements to drive innovation.