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Updated: Jun 19, 2026
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dbt Labs dbt Analytics Engineering Certification Sample Questions:
1. You introduce a custom macro into your project. This is a snippet of your dbt_project.yml:YAML
A) The macro_paths configuration in your dbt_project.yml might be incorrect or missing.
B) You must place the macros directory within the root of your dbt project.
C) The macro's name should only be 'trim', without the 'string_utils' prefix.
D) The .sql extension on the file within the macros directory is incorrect.
2. A performance-critical model depends on multiple complex transformations that would benefit from being pre-computed. Direct querying of this model should be as fast as possible. Which materialization is likely the best choice?
A) Ephemeral
B) Incremental
C) Table
D) View
3. A model depends heavily on geospatial calculations, which are computationally expensive. What optimization strategy might be worth exploring?
A) Ensure the underlying data adheres to DRY principles.
B) Convert the model to a snapshot to leverage historical data more effectively.
C) Pre-calculate common geospatial results as an incremental model.
D) Investigate whether the database offers specialized geospatial indexes or functions.
4. Your data warehouse environment undergoes a major version upgrade, introducing changes in SQL syntax and supported functions. How would you handle the migration of dbt projects to ensure compatibility?
A) All of the above.
B) Utilize custom macros to introduce conditional logic or abstract away syntax differences between versions, if feasible.
C) Thoroughly test all dbt models across your staging and development environments to identify necessary updates.
D) Create temporary branches in your dbt projects to isolate upgrade-related code changes for each environment
5. Your dbt project contains sensitive dat
a. You need to load seed data (e.g., lookup tables) while ensuring it's not accidentally committed to version control. How can you best achieve this?
A) Employ a secrets management tool and integrate it with your dbt deployment.
B) Utilize environment variables to store seed data values.
C) Create separate seed files and add them to your .gitignore or equivalent.
D) Write the seed data into log files, excluding them from version control.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: A | Question # 5 Answer: C |
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