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 onpremises 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 onpremises infrastructure to GCP.
- Implement and optimize Vertex AI solutions for advanced machine learning and AI capabilities.
- Collaborate with crossfunctional 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:
- Bachelors or Masters degree in Computer Science Information Technology or a related field.
- Minimum of 5 years of handson experience with GCP architecture and services.
- Proven experience in cloud foundation builds and onpremises 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 problemsolving skills and the ability to work in a fastpaced 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 cloudnative 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 multicloud strategies.
- Familiarity with cloud compliance frameworks such as GDPR HIPAA and SOC 2.
- Proficiency in using GCPs 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 multicloud strategies.
- Knowledge of machine learning frameworks such as TensorFlow PyTorch or scikitlearn.
- Experience with serverless computing and eventdriven 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 wellmaintained environment.
- Cost Optimization: Track cloud spending and identify opportunities for cost savings. This includes monitoring resource utilization and implementing costsaving measures.
- Migration Success Rate: Evaluate the success of onpremises 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 autoscaling 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 wellprepared and efficient incident management process.
- User Satisfaction: Gather feedback from stakeholders and endusers 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 uptodate with the latest GCP advancements.