GCP DevOps Engineer

Cloud Analytics Technologies, LLC; Dallas (TX); On-site; USD 89,000 - 126,000; Full time

Job summary

Cloud Analytics Technologies, LLC is seeking an experienced Lead GCP DevOps Engineer to lead the design, automation, security, and operational excellence of cloud-native platforms on Google Cloud Platform (GCP). You will guide GKE clusters, Terraform modules, and Harness CI/CD pipelines, while enforcing least-privilege IAM, secret management, and secure production deployments.

The role requires deep expertise in GKE, Terraform, Cloud Run/Functions, and cloud security best practices, with

Qualifications

• 10+ years of IT experience with strong DevOps and Cloud Engineering background.
• 5+ years of hands-on experience with Google Cloud Platform (GCP).
• Deep expertise with Google Kubernetes Engine (GKE) including Autopilot and Standard clusters.
• Strong experience with Terraform/Terraform Cloud for Infrastructure as Code.
• Experience building and managing Harness CI/CD pipelines.
• Strong knowledge of Docker, Kubernetes, GitHub, and Artifact Registry.
• Hands-on experience with Cloud Run, Cloud Functions, Compute Engine, and serverless deployments.
• Expertise in IAM, Workload Identity, Secret Manager, Cloud KMS, Binary Authorization, Cloud Armor, and cloud security best practices.
• Experience with Cloud SQL (PostgreSQL), Firestore, Memorystore, Cloud Storage, and Pub/Sub.
• Strong understanding of networking, load balancing, ingress, SSL/TLS certificate management, and WAF solutions.
• Experience implementing observability using Splunk, Google Cloud Monitoring, and incident management processes.
• Proficiency in Python and Bash scripting for automation.
• Experience leveraging AI tools such as GitHub Copilot, Gemini, and Claude for DevOps and automation workflows

Responsibilities

• Lead design, automation, security, and operational excellence of cloud-native platforms on GCP.
• Design, operate and upgrade GKE clusters in Autopilot and Standard modes.
• Own and maintain Terraform codebase across environments.
• Build and maintain Harness CI/CD pipelines for GKE, Cloud Run, and Cloud Functions.
• Manage edge security with Google Cloud Armor and Imperva WAF.
• Define and enforce IAM policies, Workload Identity, and Secrets management.
• Provision and manage Cloud SQL, Memorystore, Firestore, Cloud Storage, and Pub/Sub.
• Drive cost optimisation and implement autoscaling using KEDA and Custom Metrics Adapter.
• Develop automation tooling using Python/Bash; use AI tools to accelerate Terraform authoring and pipelines.

Skills

GKE

Terraform

CI/CD

Cloud security

DevOps

Kubernetes

GCP

Automation

Python/Bash

Tools

Terraform Cloud

Harness CI/CD

Artifact Registry

Cloud Run/Functions

Cloud KMS/Secret Manager

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: GCP DevOps Engineer
Location: Dallas TX
Duration: 12 Months + Extension
Bill Rate: $78/hour
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

JobDescription:

We are seeking an experienced Lead GCP DevOps Engineer to lead the design, automation, security, and operational excellence of cloud-native platforms on Google Cloud Platform (GCP). The ideal candidate will have deep expertise in GKE (Google Kubernetes Engine), Terraform, CI/CD automation, cloud security, and DevOps best practices, along with proven experience leading engineering initiatives and mentoring teams.

Kubernetes and Compute Platform :

• Design, operate, and upgrade GKE clusters in both Autopilot and Standard modes, including custom compute classes, node pool configuration, and capacity management.
  • Manage multi-cluster architecture using GKE Fleet, Multi-Cluster Ingress, and Multi-Cluster Gateway.
  • Implement workload autoscaling using KEDA and the Custom Metrics Adapter for event-driven and metrics-based scaling.
  • Manage cluster add-ons and operational tooling, including the Secrets Store CSI Driver, Reloader, ConfigMaps, and ingress configuration.
  • Deploy and operate serverless workloads on Cloud Run and Cloud Functions, and provision Compute Engine instances where required.

Infrastructure as Code :

• Own and maintain a modular Terraform codebase managed through Terraform Cloud, with environment-specific configurations across development, QA, staging, and production.
  • Build and maintain reusable Terraform modules and enforce consistent standards, reviews, and plan/apply workflows.
  • Manage Harness configuration as code through Terraform, including service, environment, and pipeline onboarding.

Networking, Edge, and Certificate Management :

• Manage global and static IP addressing, load balancing, and ingress for internet-facing and internal services.
  • Configure and maintain edge security using Google Cloud Armor and Imperva WAF.
  • Manage SSL/TLS certificates and automated certificate expiry monitoring to prevent service disruption.

Security and Identity :

• Define and enforce least-privilege IAM policies, service accounts, and Workload Identity through Terraform.
  • Enforce supply-chain security using Binary Authorization on production clusters.
  • Manage secrets through Google Secret Manager and the Secrets Store CSI Driver, and manage encryption keys in Cloud KMS, including key rotation alerting.
  • Support runtime application security tooling (e.g., Oligo) and contribute to DevSecOps practices across the delivery lifecycle.

Data and Messaging Services :

• Provision and manage Cloud SQL (PostgreSQL) instances, including database grants, certificates, backups, and performance.
  • Manage Memorystore, Firestore, and Cloud Storage resources, including access controls and lifecycle policies.
  • Support event-driven architectures built on Pub/Sub.

CI/CD and Source Control :

• Build, maintain, and optimise Harness CI/CD pipelines for GKE, Cloud Run, and Cloud Functions deployments, including progressive delivery and automated rollback.
  • Manage GitHub repositories, branching strategies, pull request workflows, and automated code review integrations.
  • Create and optimise Docker images for security, size, and build performance, and manage images in Artifact Registry.
  • Track and deliver work through Jira using agile practices.

Observability, Reliability, and Cost :

• Configure and maintain monitoring and alerting through Splunk detectors and Google Cloud Monitoring, integrated with Microsoft Teams notifications.
  • Define SLOs/SLIs, lead incident response, and conduct blameless post-incident reviews.
  • Drive cost optimisation through workload scheduling, scale-to-zero environments, rightsizing, and resource governance.

Automation and AI-Enabled Engineering :

• Develop automation and tooling using Python, Bash
  • Use AI-assisted development tools (Gemini, Claude, GitHub Copilot) to accelerate Terraform authoring, pipeline development, troubleshooting, and documentation.
  • Identify, propose, and prototype AI agents that automate DevOps workflows, such as Terraform plan review, pipeline failure analysis, incident triage, certificate and key-expiry management, IAM access requests, and cost reporting.
  • Promote responsible use of AI tools, ensuring outputs are reviewed and that sensitive data and credentials are protected.

1. Design, operate, and upgrade GKE clusters (Autopilot and Standard), including multi-cluster management with GKE Fleet, Multi-Cluster Ingress, and Multi-Cluster Gateway.

• Own and maintain the Terraform codebase in Terraform Cloud, building reusable modules and managing infrastructure consistently across development, QA, staging, and production.
• Build and optimise Harness CI/CD pipelines for GKE, Cloud Run, and Cloud Functions, including progressive delivery and automated rollback.
• Enforce least-privilege IAM, Workload Identity, and secrets management through Secret Manager, the Secrets Store CSI Driver, and Cloud KMS with key rotation monitoring.
• Strengthen platform security through Binary Authorization, Cloud Armor, and runtime application security tooling.
• Manage networking, global and static IPs, ingress, load balancing, and SSL/TLS certificate lifecycle with automated expiry monitoring.
• Provision and support data and messaging services, including Cloud SQL (PostgreSQL), Memorystore, Firestore, Cloud Storage, and Pub/Sub.
• Implement workload autoscaling using KEDA and the Custom Metrics Adapter, and manage cluster tooling such as Reloader and ConfigMaps.
• Maintain observability and alerting through Splunk detectors and Google Cloud Monitoring, define SLOs, and lead incident response and post-incident reviews.

10. Drive cloud cost optimisation through workload scheduling, scale-to-zero environments, and rightsizing.

11. Use AI tools (Gemini, Claude, GitHub Copilot) to accelerate engineering work, and identify and prototype AI agents that automate DevOps workflows such as Terraform review, pipeline failure analysis, and incident triage.

(Lead) Define the platform roadmap, set engineering standards, review designs and code, and mentor team member

Required Skills :

• 10+ years of IT experience with strong DevOps and Cloud Engineering background.
• 5+ years of hands-on experience with Google Cloud Platform (GCP).
• Deep expertise with Google Kubernetes Engine (GKE) including Autopilot and Standard clusters.
• Strong experience with Terraform/Terraform Cloud for Infrastructure as Code.
• Experience building and managing Harness CI/CD pipelines.
• Strong knowledge of Docker, Kubernetes, GitHub, and Artifact Registry.
• Hands-on experience with Cloud Run, Cloud Functions, Compute Engine, and serverless deployments.
• Expertise in IAM, Workload Identity, Secret Manager, Cloud KMS, Binary Authorization, Cloud Armor, and cloud security best practices.
• Experience with Cloud SQL (PostgreSQL), Firestore, Memorystore, Cloud Storage, and Pub/Sub.
• Strong understanding of networking, load balancing, ingress, SSL/TLS certificate management, and WAF solutions.
• Experience implementing observability using Splunk, Google Cloud Monitoring, and incident management processes.
• Proficiency in Python and Bash scripting for automation.
• Experience leveraging AI tools such as GitHub Copilot, Gemini, and Claude for DevOps and automation workflows

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.

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