Devops Engineer - Eu

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.

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 :

• Experience with ML Ops or similar
• Knowledge in advanced statistical methods

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