About the role

Role Overview

Swish Analytics is seeking a Data Engineer (remote) to support the infrastructure and delivery of its consumer and enterprise data offerings, including coverage of non-US sports. The role focuses on building and operating low-latency, real-time predictive analytics systems and production-grade data delivery pipelines.

Responsibilities

Support production systems and help triage issues during live sporting events
Architect low-latency, real-time analytics systems (raw data collection → feature development → production endpoints)
Build sports betting data products and prediction offerings
Integrate large, complex real-time datasets into consumer and enterprise products
Develop production-level predictive analytics into enterprise-grade APIs
Contribute to the design and implementation of fully automated sports data delivery frameworks

Requirements

BS/BA in Mathematics, Computer Science, or related STEM
4+ years of experience writing production code (notably Python)
Proficiency in Python and SQL (preferably MySQL)
Experience with Airflow
Experience with Kubernetes
Experience building end-to-end ETL pipelines
Experience using REST APIs
Experience with Git, CI/CD, shell scripting, and AWS infrastructure
Experience with web scraping and cleaning unstructured data
Knowledge of data science and machine learning concepts
Preferred: professional experience with MLB or NBA data

Salary

Starting at $145,000 (DOE)

About Swish Analytics

Swish Analytics is a sports analytics, betting, and fantasy startup focused on building predictive sports analytics data products. They emphasize engineering and mathematics over intuition to deliver accurate, real-time data and prediction capabilities for consumer and enterprise clients.