Sr. Cloud Platform / DevOps Engineer with Google Cloud Platform

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 6 Month(s)

Skills

Devops
GCP
AWS
Terraform
Kubernetes
GitOps workflows
DevSecOps

Job Details

Job Title: Sr. Cloud Platform / DevOps Engineer with Google Cloud Platform

Location: New York, NY (100% Remote)

Duration: 6+ Months Contracts

Description

Client seeks an Sr. Cloud Platform/DevOps engineer to augment the Cloud Platform Engineering team. The engineer will operate as an embedded engineer, supporting day-to-day sprint priorities and contributing to various cloud infrastructure, Kubernetes, CI/CD, security, and platform automation initiatives. This engagement is execution-focused, with an emphasis on Google Cloud Platform, AWS, Terraform, Kubernetes, GitOps workflows, DevSecOps, and automation-driven engineering.

Role

The engineer may be asked to contribute to one or more of the following initiatives during the engagement: Google Cloud Platform Hosted Looker Network Setup (Prod Environment) Potential Deliverables:

  • Production-ready Google Cloud Platform network configuration for Hosted Looker
  • Terraform modules and GitOps-reviewed deployment artifacts Google Cloud Platform Security Audit Remediation (Project Secure) Potential Deliverables:
  • Completed InfoSec remediation items
  • Updated Terraform modules and documentation reflecting required controls FinOps Year-End Optimization & Cast.AI Expansion Potential Deliverables:
  • AWS Account cleanup and suspension
  • Identified Google Cloud Platform cost optimization opportunities (e.g. unused or orphaned resources, underutilized Cloud Platform / DevOps Consultant

Engagement Model: The consultant will work as an integrated member of the Cloud Platform Engineering team, contributing to any active sprint priorities as assigned. Work may span platform improvements, operational support, incident response, engineering execution, and cross-team collaboration. Tavant will set priorities on a weekly or sprint basis; the consultant must be able to pivot as needed and deliver high-quality, reliable engineering output. Potential Project Assignments

The consultant may be asked to contribute to one or more of the following initiatives during the engagement: Google Cloud Platform Hosted Looker Network Setup (Prod Environment)

Potential Deliverables:

  • Production-ready Google Cloud Platform network configuration for Hosted Looker
  • Terraform modules and GitOps-reviewed deployment artifacts Google Cloud Platform Security Audit Remediation (Project Secure) Potential Deliverables:
  • Completed InfoSec remediation items
  • Updated Terraform modules and documentation reflecting required controls FinOps Year-End Optimization & Cast.AI Expansion Potential Deliverables:
  • AWS Account cleanup and suspension
  • Identified Google Cloud Platform cost optimization opportunities (e.g. unused or orphaned resources, underutilized, etc.)
  • Executed right-sizing/scale-down changes
  • Cast.AI rollout updates for target clusters Credentials DB Migration (MongoDB Firestore) Potential Deliverables:
  • Firestore infrastructure and IaC configurations
  • Migration support artifacts, testing results, and documentation GKE Upgrades & Cluster Modernization Potential Deliverables:
  • Validate GKE upgrade path, provide documentations, and support
  • Updated charts, workloads, and platform components supporting upgrades General Cloud Platform Engineering Support Potential Deliverables:
  • Participate in the Systems Support channel to assist engineers with issues related to cloud services, CI/CD, Artifactory, Terraform, Kubernetes, and platform tooling
  • Identify opportunities to streamline support, reduce repetitive toil through automation, improve documentation, and enhance developer self-service
  • Ensure that larger engineering asks are properly captured in Jira, triaged, and funneled into sprint planning instead of ad-hoc or chat-only support
  • Troubleshoot deployment, build, and configuration issues in partnership with application teams
  • Improve platform reliability, observability, and operational excellence via incremental changes Required Skills & Qualifications
  • Strong experience with Google Cloud Platform and AWS cloud engineering
  • Advanced proficiency in Terraform and IaC patterns
  • Deep hands-on experience with Kubernetes (GKE) and GitOps tooling (ArgoCD preferred)
  • Solid understanding of VPC networking, IAM, and InfoSec controls Strong scripting ability (Python, Go, or Bash)
  • Excellent written and verbal communication skills; ability to support, guide, and occasionally coach engineering teams
  • Prior experience in platform engineering, infrastructure automation, or DevOps roles, etc.)
  • Executed right-sizing/scale-down changes
  • Cast.AI rollout updates for target clusters Credentials DB Migration (MongoDB Firestore)

Potential Deliverables:

  • Firestore infrastructure and IaC configurations
  • Migration support artifacts, testing results, and documentation GKE Upgrades & Cluster Modernization Potential Deliverables:
  • Validate GKE upgrade path, provide documentations, and support
  • Updated charts, workloads, and platform components supporting upgrades General Cloud Platform Engineering Support

Potential Deliverables:

  • Participate in the Systems Support channel to assist engineers with issues related to cloud services, CI/CD, Artifactory, Terraform, Kubernetes, and platform tooling
  • Identify opportunities to streamline support, reduce repetitive toil through automation, improve documentation, and enhance developer self-service
  • Ensure that larger engineering asks are properly captured in Jira, triaged, and funneled into sprint planning instead of ad-hoc or chat-only support
  • Troubleshoot deployment, build, and configuration issues in partnership with application teams
  • Improve platform reliability, observability, and operational excellence via incremental changes Required Skills & Qualifications
  • Strong experience with Google Cloud Platform and AWS cloud engineering
  • Advanced proficiency in Terraform and IaC patterns
  • Deep hands-on experience with Kubernetes (GKE) and GitOps tooling (ArgoCD preferred)
  • Solid understanding of VPC networking, IAM, and InfoSec controls Strong scripting ability (Python, Go, or Bash)
  • Excellent written and verbal communication skills; ability to support, guide, and occasionally coach engineering teams
  • Prior experience in platform engineering, infrastructure automation, or DevOps roles

Mandatory Skills

Engineer to augment the Cloud Platform Engineering team. The engineer will operate as an embedded engineer, supporting day-to-day sprint priorities and contributing to various cloud infrastructure, Kubernetes, CI/CD, security, and platform automation initiatives. This engagement is execution-focused, with an emphasis on Google Cloud Platform, AWS, Terraform, Kubernetes, GitOps workflows, DevSecOps, and automation-driven engineering.

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.