- A
Create a custom IAM role with storage.buckets.get and storage.objects.get permissions and assign it to the service account.
Why wrong: The existing roles/storage.objectViewer already includes those permissions; a custom role is not needed.
- B
Check that the service account used by the failing pipeline's Data Fusion instance has the correct permissions, and ensure that the service account is the same as the one used by working pipelines.
The root cause is likely a different service account or misconfiguration in the failing pipeline's Data Fusion instance.
- C
Disable uniform bucket-level access and add bucket ACLs for the service account.
Why wrong: Disabling uniform access is a security downgrade and not necessary; ACLs are not the issue.
- D
Add the service account as a member of the Cloud Storage bucket with the roles/storage.objectViewer role.
Why wrong: The service account already has this role at the project level; if bucket-level access is uniform, project-level roles apply. However, if the service account is from a different project, this is needed.
Quick Answer
The answer is that the failing pipeline’s Cloud Data Fusion instance uses a different service account than the working pipelines, and that instance’s service account lacks the roles/storage.objectViewer role on the bucket. This is because, despite a source plugin specifying its own service account, Cloud Data Fusion always uses the instance-level service account to authenticate with Cloud Storage when uniform bucket-level access is enabled. The plugin’s service account is ignored for bucket-level IAM checks, so even though the failing pipeline’s plugin has the correct role, the instance itself does not. On the Google Professional Data Engineer exam, this scenario tests your understanding of how Data Fusion delegates permissions—a common trap is assuming the plugin’s service account controls access, when in reality the instance’s identity is the gatekeeper. Remember: for uniform bucket-level access, the instance’s service account is the key, not the plugin’s. A useful memory tip is “Instance first, plugin last”—always verify the Data Fusion instance’s service account when debugging permission denied errors.
PDE Practice Question: Building and operationalizing data processing systems
This PDE practice question tests your understanding of building and operationalizing data processing systems. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Your team is using Cloud Data Fusion to build batch ETL pipelines that load data from Cloud Storage into BigQuery. You have several pipelines that run daily. Recently, one pipeline started failing with a 'Permission denied' error when trying to read a new CSV file uploaded to a specific Cloud Storage bucket. Other pipelines using the same bucket succeed. The failing pipeline has a Cloud Storage source plugin that uses a service account with the roles/storage.objectViewer role. The bucket has uniform bucket-level access enabled. What is likely causing the issue?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Check that the service account used by the failing pipeline's Data Fusion instance has the correct permissions, and ensure that the service account is the same as the one used by working pipelines.
The correct answer is B because the error is likely due to the Data Fusion instance's service account, not the source plugin's service account. In Cloud Data Fusion, the pipeline execution uses the service account attached to the Data Fusion instance itself to access Cloud Storage, even if the source plugin specifies a different service account. Since other pipelines using the same bucket succeed, the issue is that the failing pipeline's Data Fusion instance uses a service account that lacks the roles/storage.objectViewer role on the bucket, while working pipelines use an instance with the correct permissions.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a custom IAM role with storage.buckets.get and storage.objects.get permissions and assign it to the service account.
Why it's wrong here
The existing roles/storage.objectViewer already includes those permissions; a custom role is not needed.
- ✓
Check that the service account used by the failing pipeline's Data Fusion instance has the correct permissions, and ensure that the service account is the same as the one used by working pipelines.
Why this is correct
The root cause is likely a different service account or misconfiguration in the failing pipeline's Data Fusion instance.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Disable uniform bucket-level access and add bucket ACLs for the service account.
Why it's wrong here
Disabling uniform access is a security downgrade and not necessary; ACLs are not the issue.
- ✗
Add the service account as a member of the Cloud Storage bucket with the roles/storage.objectViewer role.
Why it's wrong here
The service account already has this role at the project level; if bucket-level access is uniform, project-level roles apply. However, if the service account is from a different project, this is needed.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that the service account specified in a plugin (e.g., Cloud Storage source) is the one used for authentication, when in fact the Data Fusion instance's service account is the effective identity for all pipeline operations.
Detailed technical explanation
How to think about this question
Cloud Data Fusion pipelines execute under the service account of the Data Fusion instance, not the service account configured in individual plugins. This is because the instance's service account is used to authenticate API calls to Google Cloud services like Cloud Storage and BigQuery during pipeline runtime. When uniform bucket-level access is enabled, IAM permissions must be granted at the bucket level, and the instance's service account must have roles/storage.objectViewer on the bucket. A common real-world scenario is when pipelines are created in different Data Fusion instances or when an instance's service account is changed without updating bucket permissions.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this PDE question test?
Building and operationalizing data processing systems — This question tests Building and operationalizing data processing systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Check that the service account used by the failing pipeline's Data Fusion instance has the correct permissions, and ensure that the service account is the same as the one used by working pipelines. — The correct answer is B because the error is likely due to the Data Fusion instance's service account, not the source plugin's service account. In Cloud Data Fusion, the pipeline execution uses the service account attached to the Data Fusion instance itself to access Cloud Storage, even if the source plugin specifies a different service account. Since other pipelines using the same bucket succeed, the issue is that the failing pipeline's Data Fusion instance uses a service account that lacks the roles/storage.objectViewer role on the bucket, while working pipelines use an instance with the correct permissions.
What should I do if I get this PDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.
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