GCP Cloud Architect

Remote, USA Full-time
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. Apply tot his job
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