Master Enterprise GCP Architecture & Data Engineering for Senior Roles
Designed for experienced engineers (3-25 years) looking to become GCP Cloud Architects, Principal Engineers, or Data Platform Engineers. This comprehensive program covers advanced GCP services, Vertex AI, BigQuery, and enterprise-scale design that distinguishes senior engineers.

What You'll Master:
Advanced GCP Architecture & Data Platform:
• Vertex AI & Generative AI - Gemini Pro, PaLM 2, Model Garden, fine-tuning, Vertex AI Studio, AI Search
• Data Engineering at Scale - BigQuery advanced optimization, Dataflow, Pub/Sub, Dataproc, data pipelines
• Compute & Containers - GCE advanced patterns, GKE production architectures, Cloud Run, Cloud Functions
• Networking - VPC advanced design, Cloud Load Balancing, Cloud Armor, Cloud CDN, Interconnect
• Storage & Databases - Cloud Storage optimization, Cloud SQL, Spanner, Bigtable, Firestore advanced patterns

Enterprise-Grade GCP Skills:
• AI/ML Platform: Generative AI with Vertex AI, custom model training, MLOps, model serving at scale
• Data Analytics: BigQuery ML, Looker, data warehousing best practices, cost optimization
• Serverless & Event-Driven: Cloud Functions, Cloud Run, Eventarc, Workflows, serverless architectures
• Infrastructure as Code: Terraform on GCP, Deployment Manager, Config Connector for GKE
• Security & Compliance: IAM advanced patterns, VPC Service Controls, Secret Manager, Binary Authorization
• Observability: Cloud Monitoring, Cloud Logging, Cloud Trace, Error Reporting, SLO/SLI frameworks
• Cost Optimization: Committed use discounts, sustained use, rightsizing, preemptible VMs
• Site Reliability Engineering: Google SRE practices, chaos engineering, incident response

Why Deepskilling for Experienced Engineers:
🚀 Career Acceleration: Transition to GCP Cloud Architect, Principal Data Engineer, SRE Lead, or Platform Engineering roles. Master the GCP+data combination that powers modern data-driven companies.

💼 Leadership & Innovation: Learn to architect GCP data platform transformations, design scalable AI systems, and lead technical initiatives. Prepare for Staff+ and principal engineering positions in cloud and data.

🎯 Advanced Career Support:
• GitHub Portfolio: Build enterprise-grade GCP solutions showcasing BigQuery data warehouses, Vertex AI applications, GKE microservices, and data pipeline automation
• LinkedIn Optimization: Position yourself as a Senior/Principal GCP Architect or Data Platform Engineer
• Thought Leadership: Publish advanced GCP architecture patterns, data engineering best practices, and GenAI on GCP content
• Network Expansion: Connect with GCP architects, data leaders, and hiring managers at Google and data-driven enterprises

🏆 What Sets This Apart:
✓ Enterprise-scale GCP architectures (petabyte-scale data platforms)
✓ Real-world case studies from Google, Spotify, Twitter/X, data-intensive companies
✓ Senior GCP Architects and Data Engineers from Google and top tech companies as mentors
✓ Hands-on labs with BigQuery optimization, Vertex AI, and production data workflows
✓ Capstone: Design and implement a complete GCP data platform with AI integration
✓ Architecture review sessions following Google Cloud Architecture Framework
✓ Preparation for GCP Professional Cloud Architect and Data Engineer certifications
✓ Career coaching for senior IC and data platform leadership transitions

Perfect for experienced engineers (3-25 years) advancing to GCP Cloud Architect, Principal Data Engineer, SRE Lead, or Data Platform Engineering leadership roles.