dbt Labs dbt Analytics Engineering Certification : dbt-Analytics-Engineering

  • Exam Code: dbt-Analytics-Engineering
  • Exam Name: dbt Analytics Engineering Certification Exam
  • Updated: Aug 09, 2026     Q & A: 359 Questions and Answers

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

SectionObjectives
Topic 1: Analytics Engineering Foundations- Modern data stack concepts (ELT vs ETL)
  • 1. Role of dbt in analytics engineering
    • 2. Warehouse-centric transformation workflows
      - SQL proficiency for analytics
      • 1. Joins, aggregations, and window functions
        • 2. Data modeling in SQL
          Topic 2: Testing and Data Quality- Data validation strategies
          • 1. CI-based validation workflows
            • 2. Schema testing practices
              - Built-in and custom tests
              • 1. Generic tests (unique, not null, relationships)
                • 2. Custom SQL tests
                  Topic 3: dbt Core Concepts- Project structure and configuration
                  • 1. dbt_project.yml configuration
                    • 2. Packages and dependencies
                      - Models and materializations
                      • 1. Views, tables, incremental models
                        • 2. Ref and source functions
                          Topic 4: Documentation and Lineage- Data lineage understanding
                          • 1. Directed acyclic graph (DAG)
                            • 2. Dependency tracking with ref()
                              - dbt documentation system
                              • 1. Auto-generated docs site
                                • 2. Model descriptions and metadata
                                  Topic 5: Deployment and Orchestration- Environments and workflows
                                  • 1. Development vs production environments
                                    • 2. Version control with Git
                                      - Running dbt in production
                                      • 1. dbt Cloud and job scheduling
                                        • 2. CI/CD integration patterns

                                          dbt Labs dbt Analytics Engineering Certification Sample Questions:

                                          1. You've added a new exposure to your project, but it doesn't appear in dbt docs. Here's part of your dbt_project.yml:YAML

                                          A) The maturity property is missing within your exposure's configuration.
                                          B) Exposures of type 'notebook' are not automatically detected by dbt docs generate.
                                          C) You haven't run dbt docs serve after making changes to your project file.
                                          D) The owner property is not correctly formatted as an email address.


                                          2. You've created a complex lineage macro, and you want to include unit tests for the macro logic itself. How might you approach this?

                                          A) Write a Jinja script that programmatically tests various input/output scenarios of your macro.
                                          B) Utilize dbt's built-in macro testing framework.
                                          C) Include test cases for the macro within your model-level schema.yml files.
                                          D) Currently, there is no standard way to directly unit test macros within a dbt project


                                          3. You've just added some schema tests to a critical model. Which command should you execute to ensure these new tests are run?

                                          A) dbt compile
                                          B) dbt seed
                                          C) dbt test
                                          D) dbt run


                                          4. You're tasked with adding functionality to your dbt project for:

                                          A) Handling slowly changing dimensions.
                                          B) Auditing data quality with comprehensive anomaly detection tests.
                                          C) Calculating complex financial metrics specific to your industry


                                          5. (Multiple Select)

                                          A) Increase the query_comment timeout setting in your dbt_project. yml
                                          B) Use CTEs or views in the source definition to pre-filter columns or apply initial transformations.
                                          C) Introduce a source snapshot to create a point-in-time copy of the data.
                                          D) Apply an incremental materialization strategy to subsequent models if appropriate.


                                          Solutions:

                                          Question # 1
                                          Answer: B
                                          Question # 2
                                          Answer: A
                                          Question # 3
                                          Answer: C
                                          Question # 4
                                          Answer: B
                                          Question # 5
                                          Answer: B,D

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