Exam Name: dbt Analytics Engineering Certification Exam
Certification Provider: dbt Labs
Corresponding Certification: Analytics Engineers
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Updated: Oct 11, 2026
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- Total Questions: 359
- Updated on: Oct 11, 2026
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- Total Questions: 359
- Updated on: Oct 11, 2026
- Price: $69.00
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dbt Labs dbt-Analytics-Engineering Exam Overview:
| Certification Vendor: | dbt Labs |
|---|---|
| Exam Name: | dbt Analytics Engineering Certification Exam |
| Exam Number: | dbt-Analytics-Engineering |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple choice, Online proctored |
| Passing Score: | 65% |
| Related Certifications: | dbt Architect Certification |
| Exam Price: | 200 USD |
| Real Exam Qty: | 65 |
| Available Languages: | English |
| Recommended Training: | dbt Certification Study Guide dbt Official Documentation |
| Exam Registration: | Official Registration Page |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online, remotely proctored; delivered via Caveon testing platform |
| Pre Condition: | SQL proficiency recommended; 6+ months practical experience with dbt Core or dbt Cloud suggested; no mandatory prerequisites |
| Official Syllabus URL: | https://www.getdbt.com/certifications/analytics-engineer-certification-exam |
dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Creating and Maintaining Documentation | 10% | - Descriptions and metadata - Documentation standards - Generating documentation |
| Topic 2: Implementing dbt Tests | 10% | - Built-in tests - Test configuration and execution - Custom tests |
| Topic 3: dbt Models Governance | 15% | - Naming conventions and standards - Version control integration - Project organization and structure |
| Topic 4: Debugging and Error Resolution | 15% | - Identifying modeling errors - Debugging techniques - Resolving data quality issues |
| Topic 5: External Dependencies | 10% | - External sources integration - Using packages - Managing snapshots |
| Topic 6: Developing dbt Models | 20% | - Model optimization
|
| Topic 7: Managing Data Pipelines | 15% | - Deployment strategies - CI/CD integration - Pipeline orchestration |
| Topic 8: Leveraging dbt State | 5% | - State management - State-aware operations |
Questions About the dbt Labs dbt Analytics Engineering Certification Package
The dbt Labs dbt Analytics Engineering Certification exam requires a score of 65% to pass, and the official registration fee is 200 USD. Knowing these numbers in advance keeps your planning honest.
Each round of the dbt-Analytics-Engineering question bank starts from the official exam objectives: experts map the syllabus, draft questions to cover it with precision, and review the result before release. When new exam points appear, the bank is updated accordingly — deliberate coverage, not guesswork.
Any details you leave with us during browsing or purchase are guarded against misuse and external threats, and they are used only to deliver your order and support. Your dbt-Analytics-Engineering purchase stays between you and us — that is a standing commitment, not a marketing line.
The dbt Labs dbt Analytics Engineering Certification exam contains 65 questions, and you will have 120 minutes minutes to complete them. Practicing under the same constraints makes exam-day pacing feel rehearsed.
SQL proficiency recommended; 6+ months practical experience with dbt Core or dbt Cloud suggested; no mandatory prerequisites
You can confirm the current eligibility requirements on the official dbt-Analytics-Engineering exam page before you register.
Many candidates combine practice questions with official training. Recommended options include:
This package includes 359 practice questions for the dbt Labs dbt Analytics Engineering Certification exam. Every answer is verified by an experienced team of experts, so you can trust what you study.
You can register for the dbt Labs dbt Analytics Engineering Certification exam through the official channels:
The dbt Labs dbt Analytics Engineering Certification practice questions are organized around the official exam objectives. Key topics include:
- dbt Models Governance (15%)
- Implementing dbt Tests (10%)
- Managing Data Pipelines (15%)
Syllabus-driven coverage means no wasted practice on irrelevant material.
dbt Labs dbt Analytics Engineering Certification Sample Questions:
You're tasked with creating a model for audit purposes. The data must be preserved exactly as it was at a specific point in time. Update frequency is low, and there's no need for additional transformations on the captured dat a. What materialization should you use?
- A. View
- B. Table
- C. Incremental
- D. Snapshot
Correct Answer: D 🗳️
Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).
You discover a downstream model, dim products, references an outdated raw dataset, raw_product_archive, intended for historical analysis and not active products. What's the most appropriate corrective action?
- A. Add a schema test to dim_products to catch potential errors.
- B. Delete the raw_product_archive source, so it can't be used accidentally.
- C. Leave it as-is since it's not actively causing any errors currently.
- D. Update the dim_products model to reference the active product dataset.
Correct Answer: D 🗳️
Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).
(Multiple Select)
- A. Defining generic tests that apply to multiple data sources.
- B. Loading configuration data for production environments that differs from development settings.
- C. Populating a lookup table with country codes.
- D. Inserting large volumes of historical transactional data for backfilling purposes.
Correct Answer: B,C 🗳️
Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).
A team member proposes directly joining multiple raw source tables into a single large model for convenience.
Which of the following is a potential long-term consequence of this approach?
- A. Incremental materialization strategies would no longer be applicable.
- B. Your DAG might inadvertently develop circular dependencies.
- C. Maintenance complexity increases as business logic or source tables change.
- D. The dbt test command might run slower due to the complex join logic.
Correct Answer: C 🗳️
Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).
A newly-hired analyst needs to update a downstream model that depends on a chain of intermediate models. To minimize the potential for disruption, how can modularity help them?
- A. Snapshots ensure that historical data won't be impacted unintentionally.
- B. With clear dependencies, they can pinpoint which upstream models to test.
- C. By using macros, modifications are limited to a single location.
- D. Incremental materializations will help verify that the changes are successful.
Correct Answer: B 🗳️
Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).
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