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Instant Download Google : Professional-Data-Engineer日本語 Questions & Answers as PDF & Test Engine

Professional-Data-Engineer日本語
  • Exam Code: Professional-Data-Engineer
  • Exam Name: Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)
  • Updated: Aug 02, 2026
  • No. of Questions: 433 Questions and Answers
  • Download Limit: Unlimited
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Career Opportunities

The certified individuals can explore a variety of job opportunities. Some of the positions that they can take up include a Software Engineer, a Cloud Architect, a Data Engineer, a Sales Engineer, a Data Scientist, a Cloud Developer, and a Kubernetes Architect, among others. The salary outlook for these job roles is an average of $128,500 per annum.

Reference: https://cloud.google.com/certification/data-engineer

Exam Overview

The Professional Data Engineer certification exam is a 2-hour test consisting of the multiple-choice and multiple-select questions. The students can take it in the English or Japanese languages. To register for and schedule the exam, you must pay the fee of $200. It is possible to sit for this test in an online proctored format at a remote location. You can also take it as an on-site proctored exam at a designated testing center.

Google Professional-Data-Engineer日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Storing the data (~20% of the exam)20%- Planning for using a data warehouse
  • 1. Mapping business requirements
  • 2. Designing the data model
  • 3. Deciding the degree of data normalization
  • 4. Defining architecture to support data access patterns
- Selecting storage systems
  • 1. Lifecycle management of data
  • 2. Analyzing data access patterns
  • 3. Planning for storage costs and performance
- Designing for a data platform
  • 1. Building a data platform using Dataplex, Dataplex Catalog, BigQuery, Cloud Storage
  • 2. Building a federated governance model for distributed data systems
- Using a data lake
  • 1. Monitoring the data lake
  • 2. Managing the lake (data discovery, access, cost controls)
  • 3. Processing data
Topic 2: Ingesting and processing the data (~20% of the exam)20%- Building and maintaining data structures and databases
  • 1. Defining data lifecycle
  • 2. Planning for analytical and operational use cases
- Performing security considerations
  • 1. Identity and Access Management (IAM)
  • 2. Data encryption
  • 3. Auditing, privacy, and compliance
- Deploying and operationalizing the pipelines
  • 1. CI/CD for data pipelines
  • 2. Job automation and orchestration (Cloud Composer, Workflows)
Topic 3: Maintaining and automating data workloads (~15% of the exam)15%- Designing for reliability and fidelity
  • 1. Performing data quality and validation checks
  • 2. Planning for monitoring and alerting
  • 3. Recovering from failures
- Monitoring data pipelines and data processes
  • 1. Logging, monitoring, and troubleshooting
  • 2. Managing quotas and resource usage
- Automating data processes
  • 1. Workflow orchestration
  • 2. Scheduling jobs
  • 3. Continuous integration and continuous deployment (CI/CD)
Topic 4: Preparing and using data for analysis (~15% of the exam)15%- Preparing data for visualization
  • 1. Preparing data for reporting and dashboards
  • 2. Connecting to Looker and other BI tools
- Sharing data securely
  • 1. Publishing datasets
  • 2. Data sharing and collaboration
Topic 5: Designing data processing systems (~30% of the exam)30%- Selecting appropriate storage technologies
  • 1. Choosing between BigQuery, Bigtable, Spanner, Cloud SQL, Cloud Storage, Firestore, Memorystore, AlloyDB
  • 2. Mapping storage options to business requirements
- Designing data pipelines
  • 1. Integrating with new data sources
  • 2. AI data enrichment
  • 3. Batch processing
  • 4. Streaming (e.g., windowing, late arriving data)
  • 5. Data acquisition and import
  • 6. Processing logic
- Designing data processing resources
  • 1. Cost optimization
  • 2. Cluster sizing and autoscaling
  • 3. Compute options (Dataflow, Dataproc, Dataplex, Cloud Functions, Cloud Run)

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