Google Cloud Professional Data Engineer

The Core Responsibilities of a Google Cloud Data Engineer
Data Collection & Ingestion – Setting up processes to collect, store, and process large volumes of structured and unstructured data from multiple sources.

Data Transformation & Processing – Cleaning, structuring, and preparing data for analysis using batch processing (BigQuery, Dataproc, Dataflow) and real-time streaming (Pub/Sub, Apache Kafka, Cloud Data Fusion).

Data Storage & Management – Selecting and implementing data storage solutions such as BigQuery, Cloud Storage, Bigtable, Cloud SQL, and Spanner.

Data Security & Compliance – Ensuring that data is encrypted, properly managed, and stored securely, while also meeting privacy regulations (GDPR, HIPAA, SOC 2, etc.).

Data Analysis & AI/ML Integration – Helping data scientists and analysts by optimizing data models, running analytics, and integrating ML models using Google Cloud’s AI/ML services.

Automation & Orchestration – Automating workflows and job scheduling using Cloud Composer, Workflows, and CI/CD pipelines to enhance efficiency and scalability.