Only H4 EAD, L2 EAD, USC
We are looking for GCP Cloud Architect in Springfield, MO – Onsite
Duration: Long term
About Us: We are a leading technology solutions provider, committed to delivering innovative and scalable cloud solutions. We are looking for a highly skilled and experienced GCP Architect to join our team and lead our cloud foundation build, on-premises GCP migration, and Vertex AI implementation projects.
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.
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.
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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aswin@rdsolutionsinc.com
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