Staff Cloud Platform Engineer

Job Duties:

• Identify, evaluate, and recommend cloud technologies and services to improve operational efficiency, leveraging Google Professional Solutions and Developer tools.
• Design and lead cloud foundations and robust GCP solutions, including networking, security, monitoring, logging, and organizational structure to support scalable cloud operations.
• Building and deploying cloud components using Terraform, coupled with continuous integration using GitHub Actions or Bitbucket Pipelines.
• Monitoring solutions with Datadog and New Relic to ensure optimal performance and reliability.
• Leading the architecture of disaster recovery solutions for large-scale applications hosted on the cloud, ensuring business continuity.
• Database migration both within Google Cloud Platform and across different cloud providers.
• Conduct extensive work with Puppet and Chef, automating infrastructure deployment and configuration management for enhanced efficiency.
• Oversee the migration of a client’s 2PB data from AWS to GCP, managing transitions from S3 to GCS and EFS to Google File Store.
• Position is based out of Chandler, Arizona HQ but telecommuting is permitted on a case-by-case basis.

Job Requirements:

Education Requirements:

• Bachelors degree in Information Technology, Computer Science, or closely related. Employer will accept a foreign degree or evaluation based on education and progressive work experience if in the same field.

Experience Requirements:

• 36 months of experience in job offered, Staff Cloud Infrastructure Engineer, Senior Devops Engineer, Senior Cloud and Data Architect, Architect Lead - Vice President, Engineer Customer Support, or closely related.

Special skills requirements:

• Experience providing cloud and hybrid-cloud infrastructure solutions on Google Cloud Platform (GCP).
• Experience in cloud architecture, artificial intelligence, and large-scale data and infrastructure platforms across Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure.
• Experience developing Artificial Intelligence applications in Healthcare and Hospitality industry
• Experience developing code related to Data Analytics, Machine Learning and Artificial Intelligence using Python.
• Experience building and managing hybrid-cloud and containerized solutions using Kubernetes.
• Experience developing and maintaining fully automated CI/CD pipelines and supporting cloud-based disaster recovery and business continuity solutions for enterprise applications.
• Experience building data pipelines to support large-scale data processing, analytics, and machine learning workloads.
• Virtualized environments, systems monitoring, capacity planning, and performance tuning, networking, VPNS, and compute infrastructure.
• Migrating complex workloads from on-prem to the cloud
• Experience using tools: Terraform, Ansible, Chef, Puppet, Packer, Jenkins, Github Actions, Gitlab Pipeline, Kubernetes, Docker, VMware, and Hyper-V.

Benefits

• Standard Benefits