Databricks Databricks-Certified-Data-Engineer-Professional Q&A - in .pdf

  • Exam Code: Databricks-Certified-Data-Engineer-Professional
  • Exam Name: Databricks Certified Data Engineer Professional Exam
  • Updated: Jul 31, 2026
  • Q & A: 250 Questions and Answers
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  • Exam Code: Databricks-Certified-Data-Engineer-Professional
  • Exam Name: Databricks Certified Data Engineer Professional Exam
  • Q & A: 250 Questions and Answers
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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

SectionObjectives
Topic 1: Databricks Lakehouse Platform Architecture- Data governance concepts (Unity Catalog basics)
- Medallion architecture (Bronze, Silver, Gold)
- Workspace and cluster architecture
Topic 2: Data Modeling and Transformation- Dimensional modeling concepts
- Spark SQL transformations
- Performance optimization techniques
Topic 3: Production Pipelines and Orchestration- Databricks Workflows
- Error handling and recovery strategies
- Job scheduling and monitoring
Topic 4: Delta Lake and Data Management- Schema evolution and enforcement
- Time travel and versioning
- Delta Lake transactions and ACID properties
Topic 5: Data Ingestion and Processing- Structured Streaming fundamentals
- ETL pipeline design patterns
- Batch and streaming ingestion with Auto Loader

Databricks Certified Data Engineer Professional Sample Questions:

1. Which statement describes the default execution mode for Databricks Auto Loader?

A) Webhook trigger Databricks job to run anytime new data arrives in a source directory; new data automatically merged into target tables using rules inferred from the data.
B) Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; the target table is materialized by directly querying all valid files in the source directory.
C) New files are identified by listing the input directory; the target table is materialized by directory querying all valid files in the source directory.
D) New files are identified by listing the input directory; new files are incrementally and idempotently loaded into the target Delta Lake table.
E) Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; new files are incrementally and impotently into the target Delta Lake table.


2. The data governance team has instituted a requirement that all tables containing Personal Identifiable Information (PH) must be clearly annotated. This includes adding column comments, table comments, and setting the custom table property "contains_pii" = true.
The following SQL DDL statement is executed to create a new table:

Which command allows manual confirmation that these three requirements have been met?

A) DESCRIBE DETAIL dev.pii test
B) SHOW TABLES dev
C) SHOW TBLPROPERTIES dev.pii test
D) DESCRIBE EXTENDED dev.pii test
E) DESCRIBE HISTORY dev.pii test


3. A data architect has designed a system in which two Structured Streaming jobs will concurrently write to a single bronze Delta table. Each job is subscribing to a different topic from an Apache Kafka source, but they will write data with the same schema. To keep the directory structure simple, a data engineer has decided to nest a checkpoint directory to be shared by both streams.
The proposed directory structure is displayed below:

Which statement describes whether this checkpoint directory structure is valid for the given scenario and why?

A) No; Delta Lake manages streaming checkpoints in the transaction log.
B) No; only one stream can write to a Delta Lake table.
C) Yes; Delta Lake supports infinite concurrent writers.
D) No; each of the streams needs to have its own checkpoint directory.
E) Yes; both of the streams can share a single checkpoint directory.


4. The DevOps team has configured a production workload as a collection of notebooks scheduled to run daily using the Jobs UI. A new data engineering hire is onboarding to the team and has requested access to one of these notebooks to review the production logic.
What are the maximum notebook permissions that can be granted to the user without allowing accidental changes to production code or data?

A) Can Run
B) Can Manage
C) No permissions
D) Can Read
E) Can Edit


5. A data engineer is configuring a Lakeflow Declarative Pipeline to process CDC (Change Data Capture) data from a source. The source events sometimes arrive out of order, and multiple updates may occur with the same update_timestamp but with different update_sequence_id.
What should the data engineer do to ensure events are sequenced correctly?

A) Use dropDuplicates() to remove out-of-order and duplicate records in LDP.
B) Use SEQUENCE BY STRUCT(event_timestamp, update_sequence_id) in AUTO CDC APIs.
C) Use a window function to sort update_sequence_id within the same partition, i.e., update_timestamp in the LDP pipeline.
D) Set track_history_column_list to [event_timestamp, event_id] in AUTO CDC APIs.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: D
Question # 3
Answer: D
Question # 4
Answer: D
Question # 5
Answer: B

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