DevOps Engineer

Summary

Join Swish Analytics, a sports analytics startup, as a DevOps Engineer. You will develop, maintain, and implement Kubernetes clusters for heavy ML workloads, collaborating with Data Science and Data Engineering teams. Responsibilities include optimizing workloads, implementing specialized infrastructure, and enforcing best practices for software deployment. You will monitor systems, respond to incidents, and provide on-call support. The ideal candidate possesses extensive experience in DevOps/DevSecOps, AWS, CI/CD pipelines, Kubernetes, and distributed systems, along with experience in machine learning pipelines. A competitive salary is offered.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

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

Benefits

Base salary:€75,00 - €85,000