Skills You Will Have
10 items
- Designed and deployed a complete, production-style ETL pipeline on GCP, end to end
- Built serverless data-processing jobs using Cloud Run and Docker
- Modeled analytical data warehouses using industry-standard schema design
- Automated and orchestrated multi-stage pipelines using GCP-native tooling
- Applied IAM security and least-privilege principles the way real cloud teams do
- Managed infrastructure as code and shipped changes through a CI/CD pipeline
- Made and defended architecture decisions (Cloud Run vs Dataflow vs Dataproc, batch vs streaming)
- Used Claude Code as a daily engineering tool for writing, debugging, and validating real pipeline code with AI assistance
- Worked with agents, MCP-connected tools, Skills, memory, and context management to run complex engineering work effectively
- Applied multi-agent, orchestration-style thinking to AI-assisted workflows, not just to pipelines