Data Engineer

Swish Analytics • San Francisco, CA

2d • Remote

About The Position

The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We’re a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.

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

Responsibilities

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level