Cloud Solutions Architect 2

HCL Global Systems Inc.

  • Austin, TX
  • 25 days ago

    Highlights

    Knowledge, Experience and understanding of cloud-based services for AWS, Microsoft Azure or GCP Knowledge, Experience and understanding of cloud-based network design principles Strong knowledge in data governance, security, and compliance in cloud environments Strong technical writing and diagramming skills, including proficiency with modeling and mapping tools (e.g., Visio), the Microsoft Office Suite (Word, Excel, and PowerPoint) and MS Project Strong analytical and problem-solving skills with experience as a technology architect for software development, data analytics, performance management system, or data warehousing project Skill analyzing technology systems capabilities, limitations, defects, and business problems to draw evidence-based conclusions and devise innovative solutions Experience and understanding of cloud computing DevOps principles Continuous Integration/Continuous Design (CI/CD). Kubernetes architecture deployment, scaling, and maintenance Support application Kubernetes cluster and serverless infrastructure, help address any associated API's pertaining to cloud infrastructure services and integrations Work on cloud automation using Ansible, Terraform, AWS cloud formation and Azure Resource Manager (ARM) templates Experience and understanding with cloud and performance monitoring, auditing logging, and operations tools such as: Sysdig Secure (CNAPP), Dynatrace, Cloud native toolsets (AWS CloudWatch, GCP Cloud Operations, Azure Monitor, OCI Monitoring, etc.).

    Numbers & Facts

    LocationAustin, TX

    Description

    Knowledge, Experience and understanding of the limitations and capabilities of computer systems, information technology equipment, applicable programming languages, computer hardware and software, and computer operating systems.
    Knowledge, Experience and understanding of new cloud technologies and the analytical services available from the major cloud services providers
    Knowledge, Experience and understanding of cloud delivery models: PaaS, SaaS, IaaS
    Knowledge, Experience and understanding of agile (scrum) methodology and scrum ceremonies.
    Knowledge, Experience and understanding of cloud-based services for AWS, Microsoft Azure or GCP
    Knowledge, Experience and understanding of cloud-based network design principles
    Strong knowledge in data governance, security, and compliance in cloud environments
    Strong technical writing and diagramming skills, including proficiency with modeling and mapping tools (e.g., Visio), the Microsoft Office Suite (Word, Excel, and PowerPoint) and MS Project
    Strong analytical and problem-solving skills with experience as a technology architect for software development, data analytics, performance management system, or data warehousing project
    Skill analyzing technology systems capabilities, limitations, defects, and business problems to draw evidence-based conclusions and devise innovative solutions
    Experience and understanding of cloud computing DevOps principles Continuous Integration/Continuous Design (CI/CD). Experience with Containerization, deploying and configuring microservices. Kubernetes architecture deployment, scaling, and maintenance
    Support application Kubernetes cluster and serverless infrastructure, help address any associated API's pertaining to cloud infrastructure services and integrations
    Work on cloud automation using Ansible, Terraform, AWS cloud formation and Azure Resource Manager (ARM) templates
    Experience and understanding with cloud and performance monitoring, auditing logging, and operations tools such as: Sysdig Secure (CNAPP), Dynatrace, Cloud native toolsets (AWS CloudWatch, GCP Cloud Operations, Azure Monitor, OCI Monitoring, etc.).
    Proficient automation skillset using a combination of command language scripting (Bash, Korn, PowerShell, Cloud CLI, Kubernetes Helm) and third-party tools
    Knowledge, Experience and understanding with declarative and imperative languages (YAML, JSON, Ruby, HCL, etc.) and tools that are leveraged (Ansible, Docker, Terraform, etc) to leverage infrastructure-as-code (IaC).
    Ability to work under pressure and successfully manage multiple overlapping deadlines, and able to handle multiple cross-agency projects
    Ability to coordinate multiple assignments/projects, set priorities, and meet deadlines
    Ability to lead and provide direction to team members
    Ability to lead the creation of best practices and procedures
    8 years+ Knowledge, Experience and understanding of the limitations and capabilities of computer systems, information technology equipment, applicable programming languages, computer hardware and software, and computer operating systems.
    8 years+ Knowledge, Experience and understanding of new cloud technologies and the analytical services available from the major cloud services providers
    8 years+ Knowledge, Experience and understanding of cloud delivery models: PaaS, SaaS, IaaS
    8 years+ Knowledge, Experience and understanding of cloud-based services for AWS, Microsoft Azure or GCP
    8 years+ Knowledge, Experience and understanding of cloud-based network design principles
    Experience and understanding of cloud computing DevOps principles Continuous Integration/Continuous Design (CI/CD). Experience with Containerization, deploying and configuring microservices. Kubernetes architecture deployment, scaling, and maintenance
    8 years+ Knowledge, Experience and understanding with declarative and imperative languages (YAML, JSON, Ruby, HCL, etc.) and tools that are leveraged (Ansible, Docker, Terraform, etc) to leverage infrastructure-as-code (IaC).
    Knowledge and/or hands-on experience with cloud database services (Rational/NoSQL and SQL/Oracle) data lakes and cloud ETL/ELT best practices, suitable frameworks of handling all types of data for structured and unstructured information.
    8 years+ of experience architecting, engineering, or developing enterprise IT solutions in cloud and hybrid environments.
    Knowledge of AI services and configuration required to set up the service available from major cloud services providers.
    Knowledge of data pipelines, ETL processes, and big data frameworks

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