Senior Data Engineer

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

The Swish Analytics team is seeking Senior Data Engineers to have direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings. 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.

Duties

• 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
• Support production systems and help triage issues during live sporting events
• 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 5+ years of demonstrated experience writing production level code (Python)
• Proficiency in Python and SQL (preferably MySQL); minimum of 5 years of experience
• 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
• Knowledge of sports betting. An understanding of US-based sports including the NFL, NBA, MLB, NHL, Tennis, College Football/Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets

Salary: $120,000 - 165,500