Track Google Professional Data Engineer practice status, review certification scope, and request IT Mastery coverage.
Professional Data Engineer is Google Cloud’s technical data route for candidates who design, build, operationalize, secure, and monitor data processing systems on Google Cloud.
This page tracks the Professional Data Engineer practice-bank rollout for IT Mastery. Dedicated simulator practice is not live yet, but you can review the certification snapshot, topic coverage, and related live data-platform practice options while coverage is being prioritized.
| Area | Practical focus |
|---|---|
| Designing data processing systems | Choose batch, streaming, storage, warehouse, and analytics patterns. |
| Building and operationalizing systems | Implement pipelines and make them reliable, observable, and maintainable. |
| Operationalizing machine learning models | Understand data and ML handoff points without losing governance or reliability. |
| Ensuring solution quality | Secure data, monitor pipelines, improve performance, and manage cost. |
| If you need to practice… | Best page | Why |
|---|---|---|
| Google Cloud implementation basics | ACE | Best live Google Cloud route for IAM, projects, networking, operations, and troubleshooting. |
| AWS data engineering | DEA-C01 | Strong live route for ingestion, transformation, storage, and governed data pipelines. |
| Databricks data engineering | Databricks Data Engineer Associate | Useful live lakehouse route for pipeline and data workflow judgment. |
| Snowflake data engineering | SnowPro Advanced: Data Engineer | Good live route for data pipelines, loading, transformations, and platform operations. |