DevOps Engineer

Prediktive - Latin America, LATAM

We are looking for a DevOps Engineer based anywhere in Latin America to work on a long term project for one of our clients, a Data Analytics and Business Intelligence services company based in Los Angeles.

The Sr. DevOps Engineer will support our client's organization across teams by helping implement best practices and an automated approach to managing their cloud infrastructure hosted on Google Cloud Platform.

Key Responsibilities

  • Establish a practice of managing infrastructure as code
  • Manage cloud infrastructure consisting of legacy Windows VMs and cloud native resources
  • Define and implement best practices related to IaC, security, disaster recovery and cost controls
  • Develop a continuous deployment pipeline for infrastructure changes
  • Maintain infrastructure components such as VPC network, firewalls, servers, storage, databases
  • Educate engineering teams on Infrastructure As Code practices

Requirements

  • Experience managing AWS or Google Cloud infrastructure
  • Experience doing infrastructure automation using tools like Terraform, CloudFormation or Cloud Deployment Management
  • Experience doing Configuration Management with Ansible, Puppet or Chef
  • Proficient with container technologies like Docker and tools like Packer
  • Demonstrated ability to troubleshoot, problem solve, test, and develop solutions independently
  • Ownership mindset and capable of self managing tasks, scope and priorities
  • Experience implementing and managing APM such as StackDriver, Datadog, NewRelic
  • Experience managing Kubernetes clusters
  • Strong knowledge of scripting using languages such as Bash, Python or Powershell

Expected Outcomes (first 12 months)

  • Develop a continuous delivery pipeline to provision machines into GCP
  • Terraform and Ansible are standard tools for managing deployments
  • Translate security recommendations into infrastructure improvements
  • Migration from windows instances to linux/cloud native when possible
  • Reduce cost through automation and containerization for workloads
  • Engineering team is able to deploy resources through delivery pipeline


Posted On: Friday, April 19, 2019



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