# Google Cloud Engineer
Location: Remote (US)
Salary Range: $150,000 - $195,000
Employment Type: Full-time
---
[Company] is a cloud-first platform leveraging Google Cloud Platform to power our data-driven infrastructure. We process petabytes of data through BigQuery, manage containerized workloads on GKE, and build scalable serverless applications using Cloud Functions and Cloud Run. Our platform serves millions of users with 99.9% uptime across multi-region deployments.
Our engineering team builds on GCP's strengths in data analytics, machine learning, and Kubernetes orchestration. We run entirely on Google Cloud, spending $300K+ monthly across compute, storage, and data services. If you're passionate about GCP architecture and want to work with BigQuery, GKE, and modern cloud-native technologies, this is the role for you.
---
We're looking for a Google Cloud Engineer to join our Cloud Platform team. You'll design and build infrastructure on GCP—from optimizing BigQuery data warehouses processing terabytes daily to managing GKE clusters running thousands of containers. This role combines architecture design with hands-on implementation of production systems.
You'll work closely with data engineers, ML teams, and product engineers to design scalable GCP solutions, optimize costs, and establish best practices. The ideal candidate has deep experience with GCP services, understands BigQuery optimization, and excels at Kubernetes orchestration with GKE.
---
- Design and deploy highly available, cost-optimized GCP architectures
- Optimize BigQuery queries and data pipelines to reduce costs by 25%
- Scale GKE clusters to handle 10x traffic growth
- Implement Infrastructure as Code using Terraform for all GCP resources
- Establish security best practices with IAM policies and service accounts
---
- Design and implement GCP infrastructure using core services: Compute Engine, Cloud Storage, VPC networking
- Optimize BigQuery data warehouses: query performance, partitioning, clustering, and cost management
- Manage and scale GKE (Google Kubernetes Engine) clusters for containerized workloads
- Build serverless applications using Cloud Functions and Cloud Run
- Write Infrastructure as Code using Terraform for GCP resource provisioning
- Configure and manage VPCs, Cloud Load Balancing, and network architectures
- Implement IAM policies and service accounts following least-privilege principles
- Set up monitoring, alerting, and logging using Cloud Monitoring and Cloud Logging
- Optimize GCP costs through sustained use discounts, committed use contracts, and right-sizing
- Automate infrastructure provisioning and deployment pipelines
- Participate in on-call rotation for critical infrastructure (1 week every 6 weeks)
- Document architecture decisions and create runbooks for operational procedures
- Mentor junior engineers on GCP best practices and cloud architecture patterns
---
- 4+ years of professional experience with Google Cloud Platform in production environments
- Deep knowledge of core GCP services: Compute Engine, Cloud Storage, BigQuery, GKE, Cloud Functions, IAM, VPC
- Strong BigQuery experience: query optimization, partitioning, clustering, data modeling
- Hands-on experience with GKE (Google Kubernetes Engine) for container orchestration
- Infrastructure as Code experience with Terraform or Deployment Manager
- Experience designing multi-region GCP architectures
- Solid understanding of GCP networking: VPCs, subnets, firewall rules, Cloud Load Balancing
- Strong scripting skills in Python, Bash, or Go
- Understanding of CI/CD pipelines and GitOps workflows
- Experience with GCP cost management and optimization strategies
- Security-first mindset with IAM and service account best practices
---
- GCP Professional-level certification (Cloud Architect, Data Engineer, or DevOps Engineer)
- Experience with GCP data services: BigQuery, Dataflow, Pub/Sub, Cloud Storage
- Knowledge of serverless patterns: Cloud Functions, Cloud Run, Eventarc
- Experience with Vertex AI for machine learning pipelines
- Background in data engineering or analytics workloads
- Experience with multi-cloud architectures (GCP + AWS/Azure)
- Knowledge of compliance frameworks (SOC 2, HIPAA) on GCP
- Contributions to open-source infrastructure tooling
- Experience with disaster recovery planning and implementation on GCP
---
- Compute: Compute Engine, GKE (Google Kubernetes Engine), Cloud Run
- Serverless: Cloud Functions, Cloud Run, Eventarc
- Storage: Cloud Storage, Cloud SQL, Firestore
- Data: BigQuery, Dataflow, Pub/Sub, Cloud Storage
- Networking: VPC, Cloud Load Balancing, Cloud CDN, Cloud Armor
- Security: IAM, Cloud KMS, Secret Manager, Cloud Armor
- Infrastructure as Code: Terraform (primary), Deployment Manager
- CI/CD: GitHub Actions, Cloud Build, Cloud Deploy
- Monitoring: Cloud Monitoring, Cloud Logging, Cloud Trace
- ML: Vertex AI, AutoML, TensorFlow
---
- Base Salary: $150,000 - $195,000 depending on experience
- Equity: Stock options with standard 4-year vesting and 1-year cliff
- Health Insurance: 100% coverage for medical, dental, and vision (employee + dependents)
- 401(k): 4% company match, immediate vesting
- PTO: Unlimited vacation with 15-day minimum encouraged
- Remote Work: Fully remote within the US, with optional quarterly team gatherings
- Learning Budget: $3,000 annual allowance for certifications, courses, and conferences
- GCP Certification: Company-paid GCP certification exams and prep courses
- Equipment: MacBook Pro M3 and $1,500 home office stipend
- Parental Leave: 14 weeks paid leave for all new parents
- On-Call Compensation: $500/week when serving as primary on-call
---
1. Application Review — We review your resume and any relevant GCP projects (2-3 days)
2. Recruiter Screen — 25-minute call to discuss the role, your background, and answer questions
3. Technical Screen — 45-minute conversation about GCP architecture, BigQuery optimization, and past projects
4. Architecture Design — 60-minute session to design a multi-region, highly available system on GCP
5. GCP Deep Dive — 60-minute hands-on discussion about BigQuery, GKE, Terraform, and cost optimization
6. Team Conversations — Meet 2-3 team members to discuss collaboration and culture
7. Offer — Decision within 3 business days of final interview
We provide feedback at every stage and aim to complete the process within 2-3 weeks.
---
[Company] is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
We encourage applications from candidates who may not meet every requirement—research shows underrepresented groups are less likely to apply unless they meet all qualifications. If you're excited about this role, we'd love to hear from you.
# Google Cloud Engineer
**Location:** Remote (US)
**Salary Range:** $150,000 - $195,000
**Employment Type:** Full-time
---
## About [Company]
[Company] is a cloud-first platform leveraging Google Cloud Platform to power our data-driven infrastructure. We process petabytes of data through BigQuery, manage containerized workloads on GKE, and build scalable serverless applications using Cloud Functions and Cloud Run. Our platform serves millions of users with 99.9% uptime across multi-region deployments.
Our engineering team builds on GCP's strengths in data analytics, machine learning, and Kubernetes orchestration. We run entirely on Google Cloud, spending $300K+ monthly across compute, storage, and data services. If you're passionate about GCP architecture and want to work with BigQuery, GKE, and modern cloud-native technologies, this is the role for you.
---
## The Role
We're looking for a Google Cloud Engineer to join our Cloud Platform team. You'll design and build infrastructure on GCP—from optimizing BigQuery data warehouses processing terabytes daily to managing GKE clusters running thousands of containers. This role combines architecture design with hands-on implementation of production systems.
You'll work closely with data engineers, ML teams, and product engineers to design scalable GCP solutions, optimize costs, and establish best practices. The ideal candidate has deep experience with GCP services, understands BigQuery optimization, and excels at Kubernetes orchestration with GKE.
---
## Objectives
- Design and deploy highly available, cost-optimized GCP architectures
- Optimize BigQuery queries and data pipelines to reduce costs by 25%
- Scale GKE clusters to handle 10x traffic growth
- Implement Infrastructure as Code using Terraform for all GCP resources
- Establish security best practices with IAM policies and service accounts
---
## Responsibilities
- Design and implement GCP infrastructure using core services: Compute Engine, Cloud Storage, VPC networking
- Optimize BigQuery data warehouses: query performance, partitioning, clustering, and cost management
- Manage and scale GKE (Google Kubernetes Engine) clusters for containerized workloads
- Build serverless applications using Cloud Functions and Cloud Run
- Write Infrastructure as Code using Terraform for GCP resource provisioning
- Configure and manage VPCs, Cloud Load Balancing, and network architectures
- Implement IAM policies and service accounts following least-privilege principles
- Set up monitoring, alerting, and logging using Cloud Monitoring and Cloud Logging
- Optimize GCP costs through sustained use discounts, committed use contracts, and right-sizing
- Automate infrastructure provisioning and deployment pipelines
- Participate in on-call rotation for critical infrastructure (1 week every 6 weeks)
- Document architecture decisions and create runbooks for operational procedures
- Mentor junior engineers on GCP best practices and cloud architecture patterns
---
## Required Skills
- 4+ years of professional experience with Google Cloud Platform in production environments
- Deep knowledge of core GCP services: Compute Engine, Cloud Storage, BigQuery, GKE, Cloud Functions, IAM, VPC
- Strong BigQuery experience: query optimization, partitioning, clustering, data modeling
- Hands-on experience with GKE (Google Kubernetes Engine) for container orchestration
- Infrastructure as Code experience with Terraform or Deployment Manager
- Experience designing multi-region GCP architectures
- Solid understanding of GCP networking: VPCs, subnets, firewall rules, Cloud Load Balancing
- Strong scripting skills in Python, Bash, or Go
- Understanding of CI/CD pipelines and GitOps workflows
- Experience with GCP cost management and optimization strategies
- Security-first mindset with IAM and service account best practices
---
## Preferred Skills
- GCP Professional-level certification (Cloud Architect, Data Engineer, or DevOps Engineer)
- Experience with GCP data services: BigQuery, Dataflow, Pub/Sub, Cloud Storage
- Knowledge of serverless patterns: Cloud Functions, Cloud Run, Eventarc
- Experience with Vertex AI for machine learning pipelines
- Background in data engineering or analytics workloads
- Experience with multi-cloud architectures (GCP + AWS/Azure)
- Knowledge of compliance frameworks (SOC 2, HIPAA) on GCP
- Contributions to open-source infrastructure tooling
- Experience with disaster recovery planning and implementation on GCP
---
## Tech Stack
- **Compute:** Compute Engine, GKE (Google Kubernetes Engine), Cloud Run
- **Serverless:** Cloud Functions, Cloud Run, Eventarc
- **Storage:** Cloud Storage, Cloud SQL, Firestore
- **Data:** BigQuery, Dataflow, Pub/Sub, Cloud Storage
- **Networking:** VPC, Cloud Load Balancing, Cloud CDN, Cloud Armor
- **Security:** IAM, Cloud KMS, Secret Manager, Cloud Armor
- **Infrastructure as Code:** Terraform (primary), Deployment Manager
- **CI/CD:** GitHub Actions, Cloud Build, Cloud Deploy
- **Monitoring:** Cloud Monitoring, Cloud Logging, Cloud Trace
- **ML:** Vertex AI, AutoML, TensorFlow
---
## Compensation and Benefits
- **Base Salary:** $150,000 - $195,000 depending on experience
- **Equity:** Stock options with standard 4-year vesting and 1-year cliff
- **Health Insurance:** 100% coverage for medical, dental, and vision (employee + dependents)
- **401(k):** 4% company match, immediate vesting
- **PTO:** Unlimited vacation with 15-day minimum encouraged
- **Remote Work:** Fully remote within the US, with optional quarterly team gatherings
- **Learning Budget:** $3,000 annual allowance for certifications, courses, and conferences
- **GCP Certification:** Company-paid GCP certification exams and prep courses
- **Equipment:** MacBook Pro M3 and $1,500 home office stipend
- **Parental Leave:** 14 weeks paid leave for all new parents
- **On-Call Compensation:** $500/week when serving as primary on-call
---
## Interview Process
1. **Application Review** — We review your resume and any relevant GCP projects (2-3 days)
2. **Recruiter Screen** — 25-minute call to discuss the role, your background, and answer questions
3. **Technical Screen** — 45-minute conversation about GCP architecture, BigQuery optimization, and past projects
4. **Architecture Design** — 60-minute session to design a multi-region, highly available system on GCP
5. **GCP Deep Dive** — 60-minute hands-on discussion about BigQuery, GKE, Terraform, and cost optimization
6. **Team Conversations** — Meet 2-3 team members to discuss collaboration and culture
7. **Offer** — Decision within 3 business days of final interview
We provide feedback at every stage and aim to complete the process within 2-3 weeks.
---
## Equal Opportunity Statement
[Company] is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
We encourage applications from candidates who may not meet every requirement—research shows underrepresented groups are less likely to apply unless they meet all qualifications. If you're excited about this role, we'd love to hear from you.
