Microservices & API Engineer

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.

The Microservices and APIs team owns all internal and external data centric interfaces. You will be working on a system of globally distributed services and data that offer the lowest latencies in the industry. We’re looking for experienced engineers who can leverage their expertise to build the next generation of services and APIs at Swish. This position is 100% remote.

• Design, build, and optimize low latency, highly available core API services
• Assist in developing a platform and SDK for internal teams to build their services
• Work with the Swish infrastructure team to optimize the existing API service architecture and strategy
• Participate in code reviews and knowledge sharing with teams and team members
• Influence the technical direction of distributed services at Swish

• 3+ years of production level API / Microservice development
• Production experience working with Javascript (NodeJS), Python, Go, or similar
• Hands-on production experience with Kafka (confluent), Redis, MySQL, S3 or similar
• Passionate about reliability, high availability, automation, observability, coding standards and global scale
• BS degree or higher in CS/CE/SE or relevant experience 

• Experience with gRPC and Protobuf
• Experience with service discovery optimization
• Experience with various API gateway technologies
• Experience with low latency globally distributed data