Competencies: Cloud > Google Cloud Platform

GCP Fundamentals

Core GCP services and differentiators including Compute Engine, Cloud Storage, BigQuery analytics, GKE for Kubernetes, and IAM. Known for data analytics and machine learning capabilities.

Medium

Cloud Engineer, Data Engineer, ML Engineer

Compute Engine

VM instances, instance groups, preemptible VMs, sole-tenant nodes, custom machine types

Medium

Cloud Engineer, DevOps Engineer, Infrastructure Engineer

VPC & Networking

Shared VPC, VPC peering, Cloud NAT, Cloud Interconnect, firewall rules, Cloud Armor

Medium

Cloud Engineer, Network Engineer, Solutions Architect

Cloud Storage

Buckets, object lifecycle, storage classes, signed URLs, transfer service

Medium

Cloud Engineer, Data Engineer, Backend Developer

BigQuery

Serverless data warehouse, SQL analytics, partitioning, clustering, ML integration

High

Data Engineer, Analytics Engineer, ML Engineer

GKE

Managed Kubernetes, Autopilot mode, node pools, Workload Identity, Anthos

Medium

DevOps Engineer, Platform Engineer, SRE

Cloud Functions & Run

Serverless compute, event triggers, Cloud Run containers, concurrency

Medium

Backend Developer, DevOps Engineer, Cloud Engineer

IAM & Organization

Resource hierarchy, IAM roles, service accounts, organization policies, workload identity

Medium

Cloud Security Engineer, Cloud Engineer, Platform Engineer

Cloud SQL & Spanner

Managed databases, high availability, Cloud Spanner global distribution

Medium

Cloud Engineer, DBA, Backend Developer

Pub/Sub & Dataflow

Message queues, event streaming, Apache Beam pipelines, real-time processing

High

Data Engineer, Backend Developer, ML Engineer

Vertex AI & ML

AutoML, custom models, MLOps pipelines, feature store, model registry

High

ML Engineer, Data Scientist, AI Engineer

GCP Fundamentals

Awareness

Minimal exposure — understand GCP exists and its differentiators (BigQuery, GKE)

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No GCP experience whatsoever