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GCP Cloud Architect

Worldwide Salaried Open

GCP Cloud Architect - 100% REMOTE Job Description: Responsibilities:

  • Design and implement robust cloud architectures on Google Cloud Platform (GCP).
  • Lead the cloud foundation build, ensuring best practices in security, scalability, and performance.
  • Manage and execute the migration of on-premises infrastructure to GCP.
  • Implement and optimize Vertex AI solutions for advanced machine learning and AI capabilities.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Provide technical leadership and mentorship to junior engineers and architects.
  • Ensure compliance with industry standards and regulatory requirements.
  • Troubleshoot and resolve complex technical issues related to GCP infrastructure and services.
  • Stay updated with the latest GCP features, tools, and best practices.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
  • Minimum of 5 years of hands-on experience with GCP architecture and services.
  • Proven experience in cloud foundation build and on-premises to GCP migration projects.
  • Strong expertise in Vertex AI and implementing machine learning models on GCP.
  • Proficiency in GCP services such as Compute Engine, Cloud Storage, BigQuery, Cloud Functions, and Kubernetes Engine.
  • Excellent understanding of networking, security, and IAM in GCP.
  • Strong problem-solving skills and the ability to work in a fast-paced environment.
  • Excellent communication and collaboration skills.

Technical Skills Required:

  • Experience with Terraform, Ansible, or other infrastructure as code (IaC) tools.
  • Knowledge of DevOps practices and CI/CD pipelines.
  • Proficiency in scripting languages such as Python, Bash, or PowerShell.
  • Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
  • Familiarity with monitoring and logging tools such as Stackdriver, Prometheus, and Grafana.
  • Understanding of data engineering concepts and tools like Dataflow, Dataproc, and Pub/Sub.
  • Experience with API management and microservices architecture.
  • Knowledge of security best practices, including encryption, key management, and identity management.
  • Familiarity with other cloud platforms like AWS or Azure.
  • Experience with cloud-native application development and serverless architectures.
  • Proficiency in designing and implementing disaster recovery and business continuity plans.
  • Knowledge of cloud cost management and optimization strategies.
  • Experience with hybrid cloud environments and multi-cloud strategies.
  • Familiarity with cloud compliance frameworks such as GDPR, HIPAA, and SOC 2.
  • Proficiency in using GCP's AI and machine learning tools, such as AutoML and AI Platform.
  • Experience with data warehousing solutions like BigQuery and data lake architectures.
  • Knowledge of cloud networking concepts, including VPC, VPN, and interconnects.

Preferred Skills:

  • GCP Professional Cloud Architect certification.
  • Experience with hybrid cloud environments and multi-cloud strategies.
  • Knowledge of machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with serverless computing and event-driven architectures
  • Key performance indicators (KPIs) for a GCP Architect can help measure the effectiveness and success of their work. Here are some important KPIs to consider:
  • Cloud Infrastructure Uptime: Measure the availability and reliability of the cloud infrastructure. High uptime indicates a stable and well-maintained environment.
  • Cost Optimization: Track cloud spending and identify opportunities for cost savings. This includes monitoring resource utilization and implementing cost-saving measures.
  • Migration Success Rate: Evaluate the success of on-premises to GCP migration projects. This includes the percentage of successful migrations completed on time and within budget.
  • Performance Metrics: Monitor the performance of cloud applications and services, including response times, latency, and throughput. Ensure that performance meets or exceeds predefined SLAs.
  • Security Compliance: Ensure that the cloud environment adheres to security best practices and compliance requirements. This includes regular security audits and vulnerability assessments.
  • Scalability and Flexibility: Measure the ability to scale resources up or down based on demand. This includes the efficiency of auto-scaling mechanisms and the flexibility of the architecture.
  • Incident Response Time: Track the time taken to detect, respond to, and resolve incidents. Faster response times indicate a well-prepared and efficient incident management process.
  • User Satisfaction: Gather feedback from stakeholders and end-users to assess their satisfaction with the cloud solutions provided. High satisfaction levels indicate successful implementation and support.
  • Innovation and Improvement: Measure the frequency and impact of new features, improvements, and optimizations introduced to the cloud environment. This includes the adoption of new GCP services and technologies.
  • Training and Development: Track the ongoing training and certification of the cloud team. Continuous learning and skill development are crucial for staying up-to-date with the latest GCP advancements.

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