What are the responsibilities and job description for the Cloud Engineer position at Genisis Technology Solutions Inc?
Job Details
Responsibilities
- Function as a key member of the team responsible for the day-to-day, 24x7x365 on-call engineering, system administration, and operation of Paybox Cloud systems.
- Provide review and input into the design of new technical features and architectural changes to the systems.
- Define and implement best practices around various operation processes.
- Perform periodic software updates to systems, and address security vulnerabilities.
- Scale infrastructure to meet growing capacity and launch new applications in both private and public clouds.
- Lead troubleshooting efforts to find root causes and corrective actions throughout the life of a project.
- Develop tools to automate builds and continuous integration using Octopus Deploy, Jenkins, Terraform, Docker, Kubernetes, etc.
- Develop monitoring solutions and appropriate metrics to measure performance and efficiency of applications using the ELK stack and/or Datadog.
- Own the day-to-day health, uptime, monitoring, and reliability of services.
- Participation in an on-call rotation for after-hours coverage as needed.
- Other duties as assigned.
- Position may require some travel.
Desired Background
- Certification: AWS Certified SysOps Administrator Associate.
- Bachelor's degree in Computer Science, Information Technology, Management Information Systems, related field or equivalent experience.
- 3 years experience in a 247 high-availability production environment.
- 3 years experience with System Engineering in private and/or public cloud data center environments.
- 5 years experience working with Windows and Linux based server systems such as Windows Server 2008 2016, CentOS, CoreOS, and Ubuntu.
- In depth understanding of TCP/IP LAN/WAN networking technologies and troubleshooting techniques.
- Experience with infrastructure health monitoring and capacity planning using tools such as Solarwinds Orion, Prometheus, Grafana, Elasticsearch, Datadog, etc.
- Experience with hardware or software-based firewalls, load balancers and proxy servers.
- Experience with intrusion detection systems and network and server security hardening.
- Experience with virtualization technologies such as VMWare and KVM.
- Experience with container management platforms (Kubernetes) and container runtimes (Docker).
- Good knowledge of languages such as Python, JavaScript and PowerShell.
- Excellent organizational skills, and oral and written communication skills.
- Ability to work with minimal supervision, making decisions based upon priorities, schedules and an understanding of business initiatives.
- Critical attention to detail, thoroughness and documentation.
Preferred Qualifications
- Certification: AWS Certified DevOps Engineer Professional.
- Previous DevOps experience to act as liaison between development and quality assurance teams as part of the SDLC process.
- Experience with public cloud service providers such as Amazon AWS, Microsoft Azure, Google Google Cloud Platform, etc.
- Experience with deploying server workloads in a multi-tier architecture.
- Experience in REST and SOAP distributed application troubleshooting.
- Experience with cloud data protection and backup operations to support DR/BCP solutions for cloud workloads.
- Experience with relational and NoSQL database technologies.
- Extensive experience with configuration management and infrastructure as code using YAML and tools such as SaltStack, Ansible, Terraform, CloudFormation.
- Experience with CI/CD and automated software delivery pipelines using tools such as Octopus Deploy, Jenkins and Terraform.
- Experience monitoring solutions and appropriate metrics to measure performance and efficiency of applications using tools such as ELK stack and/or Datadog.
- Experience with source control systems such as VSTS, Azure DevOps and Git.
- Experience in monitoring, metrics collection, and reporting using open source tools.
- Good knowledge in automating the management of a data center environment.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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