About the job
Lead Data Engineer - Azure, Databricks, Python
About Us
At Two Circles, we are pioneers in the Sports & Entertainment Marketing industry, dedicated to amplifying audiences and enhancing revenue streams. Our deep understanding of fan behavior allows us to empower our clients to connect with their audiences more effectively. We collaborate with renowned organizations such as the English Premier League, Red Bull, UEFA, VISA, the NFL, Nike, and Amazon, providing insights that drive growth in both direct-to-consumer and B2B sectors. With a global presence encompassing nearly 1,000 professionals across 14 offices, we are committed to delivering innovative solutions to sports and entertainment businesses worldwide.
Your Role
We are seeking an exceptional Data Engineer to join our dynamic team of over 100 Data & BI Engineers, focusing on our Audience Intelligence Platform. In this position, you will be instrumental in developing a cutting-edge data management and analytics platform tailored for the sports industry. You will leverage advanced technologies to design, create, and optimize scalable data solutions that enable teams and organizations to harness the full potential of their data. If you are passionate about data engineering and thrive in a collaborative and fast-paced environment, we encourage you to apply!
Your responsibilities will evolve as you grow, starting with:
- Designing, building, and testing scalable data platform solutions within Azure, utilizing tools such as ADF, Databricks, and Function Apps, with expertise in Python.
- Creating high-quality data products that ensure efficiency, reliability, and performance across our data pipelines.
- Collaborating closely with product and marketing teams to deliver actionable data-driven insights and solutions that are of significant business value.
- Writing clean, maintainable code in accordance with industry best practices and development frameworks, upholding robust data engineering standards.
- Continuously enhancing and optimizing data workflows, monitoring performance metrics, and implementing innovations to drive progress.

