Support production systems and help triage issues during live sporting events
Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
Build new sports betting data products and predictions offerings
Integrate large and complex real-time datasets into new consumer and enterprise products
Develop production-level predictive analytics into enterprise-grade APIs
Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

BS/BA degree in Mathematics, Computer Science, or related STEM field
Minimum of 2+ years of demonstrated experience writing production level code (Python)
Proficiency in Python and SQL (preferably MySQL)
Demonstrated experience with Airflow
Demonstrated experience with Kubernetes
Experience building end-to-end ETL pipelines
Experience utilizing REST APIs
Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
Experience with web scraping and cleaning unstructured data
Knowledge of data science and machine learning concepts
A strong interest for sports and sports betting, with an emphasis on Tennis.
An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets.

Data Engineer

Key skills