Data Engineer
$160,000–$160,000 year
RemoteUnited States
Job Summary
Support production systems and triage issues during live sporting events while architecting low-latency, real-time analytics systems for raw data collection and feature development. Build new sports betting data products and predictions offerings by integrating complex real-time datasets into consumer and enterprise APIs. Contribute to fully-automated sports data delivery frameworks using Python, SQL, Airflow, and Kubernetes to streamline ETL pipelines and cloud infrastructure. This remote role focuses on delivering accurate, predictive analytics for non-US sports coverage, leveraging deep knowledge of US leagues and machine learning concepts to inform complex dataset analysis.
Required Qualifications
- 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
- Proficiency in 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 in 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
Desired Qualifications
- The ability use your knowledge of the sport to inform your work with complex datasets
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