DevOps Engineer

Swish Analytics • Full-time • Remote (San Francisco Bay Area, US) • $140k - $190k / year • 17h ago

Company Overview

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. This position is 100% remote from PST location only.

No third-party recruiters or agencies

Responsibilities:

Use your experience to develop, maintain and implement Kubernetes clusters at scale that are ready for heavy/spiky ML workloads
Work closely with Data Science and Data Engineering teams to implement, optimize and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages
Help Data Science and Data Engineering develop and implement specialized infrastructure to deliver tools/software to improve the reliability and scalability of services
Pioneer, implement, and enforce best practices for software deployment and code management
Monitor the system and respond to incidents to maintain system SLO/SLA, review and follow up production incidents
Provide on call work as needed

Qualifications:

4+ years of experience working in a DevOps or DevSecOps role
4+ years building within AWS, including EKS, EC2, RDS, and other common AWS services using Terraform, Terragrunt or similar technologies
4+ years building CICD pipelines with Github Actions, Jenkins and ArgoCD
4+ years of experience managing, provisioning and maintaining distributed systems with containerization tools, including Kubernetes, Docker, Helm
2+ years of Python or Go experience
Have a deep understanding of distributed systems including storage, networking, and security
Have previous SRE or DevOps experience in managing customer-facing systems in a 24/7 environment
Have worked with machine learning pipelines

Preferred: