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GCP Cloud Infrastructure Engineer

Company:
HRM Global
Location:
Phoenix, AZ
Pay:
$60/hr
Posted:
July 19, 2025
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Description:

Our client is a Consultancy Services as consultant and subject matter expert for internal stakeholders in engineering, sales, customer organizations to resolve technical deployment obstacles and improve Google Cloud.

Salary: $60/hr

Job Type: Contract

Work Location Type: On site

Industry: Information Technology and Services

Experience Required (yrs): 8

Function: Information Technology

Experience Level: Mid-senior

Education Level: Bachelor’s degree

Screening Questions

What is the candidate's full legal name?

What is the candidate's Month and Day of DOB (required for submission to client as a unique identifier):

What is candidate's desired hourly pay rate?

Please provide the link to candidate’s LinkedIn profile:

Where is the candidate located? If candidate is not near the job location, please explain relocation plan in detail (e.g. timeline, relocating with family, selling/buying property)

Is the candidate legally authorized to work in the US for any employer?

Will the candidate now or in the future, require immigration sponsorship for work authorization (for example, H-1B status)?

How many years of total IT experience does the candidate have?

How many years of experience does the candidate have in the required skills?

What is the candidate’s highest degree, specialization, and education start date?

What is the candidate’s most recent company?

What is the city and state of the candidate’s most recent company?

Has the candidate ever worked for TCS? If yes, please provide their TCS Employee/BA ID.

What date is the candidate available?

You Must have:

5+ years of hands-on experience with CloudBees (Jenkins Enterprise)

Strong expertise in GCP services (IAM, VPC, GKE, Dataflow, BigQuery)

Proficiency with Terraform and Infrastructure as Code (IaC)

Solid background in Docker, Kubernetes, and Service Mesh (Istio preferred)

Experience with CI/CD, monitoring tools (Stackdriver, Prometheus), and production support at scale

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