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 enterprise clients.

In Short

Be the technical lead and owner for key products of our core backend applications.
Perform code reviews and provide constructive feedback.
Find optimizations in current applications, implement best practices, and ensure adherence to coding standards.
Design and enhance both new and existing services.
Work with globally distributed data.
Participate in discussions and create and review architectural diagrams.
Have a deep understanding of high-traffic, client-facing APIs and networking topology.

Requirements

8+ years of production software engineering and technical leadership experience.
A creative mind for solving technically difficult problems in both standard and non-standard ways.
Hands-on production experience with languages like NodeJS & Python.
Hands-on production experience with databases, both relational and non-relational.
Passionate about reliability, high availability, automation, observability, coding standards, and global scale.
Strong communication skills working with technical and non-technical stakeholders.
You have a BS or higher in CS/CE/SE or relevant experience.

Benefits

Production experience with software engineering at a global level.
Interest or experience with GO.
Production experience with stream-processing paradigms like Kafka.
Production experience with Docker and Kubernetes.
Familiarity with sports data.
Production experience working with low latent globally distributed data.
Production experience developing, deploying and maintaining critical business applications.
Understanding of various observability platforms.
Knowledge of CI/CD.