Understanding GCP pricing models and cost optimization strategies.
Architectural Design Principles like Scalability, reliability, security, performance, cost-effectiveness.
Hybrid and Multi-Cloud Architectures like Understanding how GCP integrates with on-premises and other cloud environments.
Understanding the principles, benefits, and challenges of data lakes.
Implementing policies for data access, quality, and compliance within the data lake.
Designing and implementing systems for cataloging and managing metadata within the data lake using Dataplex.
Data Ingestion Patterns like Batch and streaming data ingestion strategies.
Data Transformation and Processing frameworks suitable for data lakes.
Enabling Data Consumption and Access for various users and applications to access data in the lake.
Specific GCP Data Lake Services:
Google Cloud Storage Expertise in designing the storage layer for the data lake, including bucket organization, storage classes, and lifecycle policies.
BigQuery expertise for querying and analyzing large datasets within the data lake.
Designing and implementing data lakes with integrated governance, discovery, and security using DataPlex.
Cloud Dataflow Architecting scalable data processing pipelines for ETL/ELT within the data lake.
Cloud Dataproc Expertise Understanding how to leverage managed for data processing.
Pub/Sub & Dataflow for Streaming Designing real-time data ingestion and processing pipelines.
Infrastructure as Code Proficiency in tools like Terraform or Cloud Deployment Manager for automating infrastructure provisioning.
Security Best Practices for GCP Implementing security controls for data at rest and in transit.
Disaster Recovery and Business Continuity Designing resilient data lake architectures.
Communication and Collaboration Ability to communicate technical concepts to both technical and non-technical stakeholders.