Data Engineer
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Job Description
Data Engineer impacting the infrastructure and delivery of core data offerings for a sports analytics startup. Building new products focused on accurate and real-time data in the sports industry.
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
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 for 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
Benefits:
- Equal Opportunity Employer
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