Yoh, A Day & Zimmermann Company

Senior Azure Cloud / DevOps Engineer - hybrid 2-3 days onsite

Dallas, Texas · Senior

Sponsorship not specifiedDetected 120 days ago
GitAzureTerraformCI/CDDevOpsLoad Balancing

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Third-party placement is common here

65% of this employer's visa filings place the worker at a client company rather than at the employer itself, across 18 clients. Your visa, salary band and layoff exposure would follow the employer of record, not the client.Most common: Fidelity Investments · Sanofi · Google

Files H-1B transfers

29 transfer filings in the last year, covering 29 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Title: Senior Azure Cloud / DevOps Engineer Location: Dallas, TX Schedule: onsite 2-3 days/week Duration: 6-12 month Contract to Hire ( w2 consultants only ) PLEASE NOTE: Final interview is required to be onsite so local candidates only.
  • Must have skills and experiences Azure (Microsoft Entra Id, Azure Update Manager, Azure Virtual Desktop, API Management, Application Gateway, Load Balancer, App Services) Terraform CI/CD (pipelines) GitHub Hands-on experience with scripting (Po…
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This listing is sourced directly from Yoh, A Day & Zimmermann Company's careers page and normalized into a canonical job model.