Data Engineer

Swish Analytics

$160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • BS/BA in Mathematics, Computer Science, or related STEM field
  • 2+ years experience writing production-level code in Python
  • Proficient in Python and SQL, especially MySQL
  • Experience with Kubernetes and Airflow
  • Skilled in building end-to-end ETL pipelines
  • Proficient in utilizing REST APIs
  • Familiar with git, CI/CD, shell scripting, and AWS
  • Experience in web scraping and handling unstructured data
  • Knowledgeable in data science and machine learning concepts
  • Strong interest in sports, particularly Tennis.

Responsibilities

  • Support production systems during live sporting events and triage issues
  • Architect low-latency, real-time analytics systems for data collection and feature development
  • Develop new sports betting data products and predictive offerings
  • Integrate real-time datasets into consumer and enterprise products
  • Create production-level predictive analytics APIs
  • Design and implement automated sports data delivery frameworks

Benefits

  • Fully remote work environment
  • Opportunity to work with cutting-edge technologies
  • Impactful role in the sports prediction and data analytics space
  • Involvement in building new data products for a passionate team
  • Work directly on real-time data offerings that affect consumer experiences
Full Job Description
Job Description

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.

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

Base Salary: Starting at $160,000 - DOE

Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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