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Key Responsibilities and Required Skills for Google Cloud Platform Engineer

💰 $110,000 - $160,000

CloudGoogle Cloud Platform (GCP)DevOpsSREInfrastructure

🎯 Role Definition

We are seeking a seasoned Google Cloud Platform (GCP) Engineer to architect, deploy, and maintain production-grade cloud infrastructure and platform services on Google Cloud. The ideal candidate will be responsible for delivering secure, highly available, and cost-efficient cloud solutions using Infrastructure as Code (Terraform/Deployment Manager), container orchestration (GKE/Kubernetes), modern CI/CD pipelines (Cloud Build/Jenkins), and observability tooling (Cloud Monitoring, Logging). This role partners closely with software engineering, security, data, and product teams to drive cloud adoption, migrations, and platform improvements while enforcing best practices for security, reliability, and performance.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Cloud Engineer / Associate Cloud Engineer transitioning from on-prem or multi-cloud operations
  • Systems Administrator or Network Engineer with cloud experience
  • DevOps Engineer or Software Engineer with container and automation background

Advancement To:

  • Senior Google Cloud Platform Engineer / Senior Cloud Engineer
  • Cloud Architect / Google Cloud Architect
  • Site Reliability Engineer (SRE) / Staff SRE
  • Principal Cloud Engineer / Platform Engineering Lead
  • Engineering Manager, Cloud Platforms

Lateral Moves:

  • DevOps / Platform Engineer
  • Cloud Security Engineer
  • Data Engineer (BigQuery / Dataflow-focused)
  • Site Reliability Engineer (SRE)
  • Solutions Architect / Technical Consultant

Core Responsibilities

Primary Functions

  • Design and implement end-to-end Google Cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform and Deployment Manager, ensuring environments are reproducible, versioned, and compliant with security and governance standards.
  • Architect, deploy, and operate Kubernetes clusters on Google Kubernetes Engine (GKE) with production-grade configurations for autoscaling, node pools, network policies, and pod security, and run secure containerized workloads using best practices.
  • Build and maintain CI/CD pipelines for automated application build, test, and deployment using Cloud Build, Jenkins, Spinnaker, or GitHub Actions, integrating security scans, unit/integration tests, and deployment strategies (canary/blue-green).
  • Implement and manage network architecture in GCP: design VPCs, subnets, Shared VPC, VPC peering, Cloud NAT, Load Balancers (HTTP(S), TCP/UDP), VPN/Interconnect, and firewall rules to meet performance, security, and multi-region availability requirements.
  • Lead cloud migration activities including discovery, lift-and-shift and refactor strategies for moving on-premises workloads and virtual machines to Compute Engine, GKE, Cloud Run, or managed services with minimal disruption.
  • Define and enforce identity and access management (IAM) policies, roles, and least-privilege access across GCP projects, folders, and organizations; integrate IAM with SSO and directory services where required.
  • Implement observability and incident response: configure Cloud Monitoring, Cloud Logging, Trace, Error Reporting, and dashboards; create actionable alerts, runbooks, SLIs/SLOs and support incident management and postmortems.
  • Optimize cloud cost and resource utilization through rightsizing, committed use discounts, sustained use discounts, and automation of lifecycle policies for compute, storage, and BigQuery to reduce monthly spend.
  • Design and operate data platform components on GCP such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage; collaborate with data engineers to ensure performant ETL and analytics pipelines.
  • Secure cloud workloads and data by implementing VPC Service Controls, encryption at rest/in-transit, key management (Cloud KMS), security scanning, vulnerability management, and automated compliance checks.
  • Create and maintain automation for infrastructure provisioning, configuration management, and environment drift remediation using Terraform, Ansible, Helm charts, or other automation frameworks.
  • Manage databases and stateful services: provision, automate backups, perform scaling, and run operations for Cloud SQL, Cloud Spanner, Bigtable, and managed caching (Memorystore).
  • Design disaster recovery and backup strategies including multi-region replication, snapshots, DR rehearsals, and RTO/RPO profiling to ensure business continuity for critical services.
  • Evaluate new GCP services and third-party tools, build proof-of-concepts (PoCs), and recommend migration or adoption strategies to improve developer productivity and platform capabilities.
  • Partner with application and security teams to conduct architecture reviews, threat modeling, and security assessments for new services and ensure alignment with compliance frameworks (SOC2, HIPAA, PCI).
  • Troubleshoot complex production issues across the stack (network, compute, storage, container runtimes, application) and lead root cause analysis with clear remediation plans and preventative measures.
  • Maintain infrastructure lifecycle management including patching strategies, OS hardening, container runtime updates, and automated image building pipelines (Packer/Google Cloud Build).
  • Implement messaging and event-driven architectures on GCP using Pub/Sub, Cloud Tasks, and streaming integrations; ensure high availability and at-least-once/at-most-once semantics as required.
  • Drive platform reliability improvements by applying SRE practices: define and measure SLAs/SLOs, error budgets, capacity planning, and incident retrospectives to reduce mean time to detect (MTTD) and mean time to recover (MTTR).
  • Create, review, and maintain clear technical documentation, runbooks, and architecture diagrams for onboarding, operational support, and audits; mentor junior engineers on cloud best practices.
  • Collaborate with product owners and engineering teams to translate business requirements into scalable cloud architectures and prioritize technical work in agile ceremonies.
  • Automate security and compliance verification in the CI pipeline (IaC scanning, container image scanning, policy-as-code using Forseti/Config Validator/OPA) to prevent drift and configuration mistakes.
  • Manage service accounts, secrets management, and secure credential rotation using Secret Manager or HashiCorp Vault, ensuring no secrets are stored in code repositories.
  • Lead vendor evaluation and procurement when selecting managed services, third-party SaaS, and observability/security tools for the GCP environment.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Provide on-call support rotations and triage production incidents, escalating and coordinating across teams until resolution.
  • Deliver internal training sessions and workshops on GCP services, Terraform patterns, Kubernetes operations, and cloud security best practices.
  • Assist in cost allocation tagging and showback/chargeback reporting to engineering teams and finance for better cloud cost visibility.
  • Participate in vendor and toolchain evaluations, pilots, and rollouts; provide recommendations grounded in technical and business tradeoffs.
  • Help maintain internal compliance artifacts and evidence for audits, including architecture diagrams, IAM policies, and configuration baselines.
  • Support proof-of-concept builds and pilot projects to validate architecture decisions and new service adoption for product teams.

Required Skills & Competencies

Hard Skills (Technical)

  • Google Cloud Platform (GCP) services deep knowledge: GKE, Compute Engine, Cloud Run, Cloud Functions, Cloud Storage, Cloud SQL, Spanner, BigQuery, Dataflow, Pub/Sub.
  • Infrastructure as Code (IaC): Terraform (preferred), Google Deployment Manager, Terragrunt—authoring, module design, and lifecycle management.
  • Kubernetes and container ecosystem: GKE administration, Helm charts, Operator patterns, kube-proxy, CNI, pod/network security policies, CI/CD integration.
  • Scripting and programming: Python, Go, or Bash for automation, tooling, and runbook automation; familiarity with Java or Node.js a plus.
  • CI/CD and automation tooling: Cloud Build, Jenkins, Spinnaker, GitOps workflows, Artifacts registry, and automated testing frameworks.
  • Networking and security: VPC design, subnets, routing, firewall rules, Cloud Armor, VPN/Interconnect, Load Balancing, TLS, and identity-aware proxy patterns.
  • Observability and monitoring: Cloud Monitoring, Cloud Logging, Trace, Error Reporting, OpenTelemetry instrumentation, Grafana/Prometheus experience beneficial.
  • Databases and data services: BigQuery, Dataflow, Dataproc, Cloud SQL, Cloud Spanner, Bigtable; ETL/ELT concepts and performance tuning on BigQuery.
  • Security and compliance: IAM, VPC Service Controls, Cloud KMS, Secret Manager, compliance frameworks (SOC2, HIPAA), infrastructure policy-as-code (OPA, Policy Controller).
  • Configuration management and automation: Ansible, Packer, Helm, Docker, CI pipelines, and automated image/bake pipelines.
  • Cost management and optimization: billing reports, committed use discounts, reservations, rightsizing, and cost governance practices.
  • Linux systems administration and troubleshooting, process monitoring, and performance tuning.
  • Version control and collaboration: Git, branching strategies, code review practices, and pull request workflows.
  • Optional but highly desirable: Google Cloud certifications (Professional Cloud Architect, Professional Cloud DevOps Engineer, Associate Cloud Engineer), Kubernetes certifications (CKA/CKAD).

Soft Skills

  • Strong written and verbal communication for cross-functional collaboration, technical documentation, and stakeholder updates.
  • Excellent troubleshooting and analytical skills with a systems-thinking mindset.
  • Ability to translate business requirements into pragmatic technical solutions and prioritize trade-offs.
  • Team player who mentors junior engineers, leads peer reviews, and fosters a culture of reliability and automation.
  • Proactive problem-solver with a continuous improvement mindset and willingness to own end-to-end platform outcomes.
  • Comfortable working in an agile environment, participating in sprint planning, standups, and retrospectives.
  • Strong customer orientation: ability to partner with product and engineering teams to deliver value quickly and safely.
  • Effective time management, prioritization, and the ability to balance operational and project work.
  • Calm and methodical during incidents, able to lead postmortems and implement long-term fixes.
  • Adaptability and eagerness to learn new GCP features and cloud-native technologies as the platform evolves.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related technical field, or equivalent practical experience.

Preferred Education:

  • Master's degree in Computer Science or related technical discipline or significant relevant industry experience.
  • Relevant certifications such as Google Professional Cloud Architect, Professional Cloud DevOps Engineer, or Associate Cloud Engineer.

Relevant Fields of Study:

  • Computer Science
  • Cloud Computing / Distributed Systems
  • Software Engineering
  • Networking / Information Security

Experience Requirements

Typical Experience Range: 3 - 8 years of hands-on experience in cloud engineering, platform engineering, or DevOps roles.

Preferred:

  • 5+ years of experience designing and operating production cloud infrastructure, with at least 2+ years focused on Google Cloud Platform (GCP).
  • Demonstrated experience with Terraform-based IaC, Kubernetes (GKE), CI/CD automation, and GCP-native observability and security tooling.
  • Proven track record of leading migrations, cost optimization efforts, and cross-functional platform initiatives.
  • Experience participating in on-call rotations, incident response, and SRE practices.

Certifications recommended: Google Cloud Professional Cloud Architect, Google Cloud Professional Cloud DevOps Engineer, Certified Kubernetes Administrator (CKA), HashiCorp Terraform Associate.

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