Data Engineer

Duties

• 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

Requirements

• 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 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, and the ability use your knowledge of the sport to inform your work with complex datasets

Qualifications

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law.