Swish Analytics is looking to solve the challenge of oddsmaking through engineering, mathematics, and sports betting expertise by building the next generation of predictive sports analytics data products. They need Senior Data Engineers to impact the infrastructure and delivery of their core consumer and enterprise data offerings, focusing on accurate predictions and real-time data using the latest technologies.
Requirements
- 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)
Responsibilities
- 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
Other
- BS/BA degree in Mathematics, Computer Science, or related STEM field
- Experience with web scraping and cleaning unstructured data
- Knowledge of data science and machine learning concepts
- Knowledge of sports betting
- Must have knowledge and understanding of NBA OR NFL and the ability use your knowledge of the sport to inform your work with complex datasets
