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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer is evaluating tools to build a production-grade data pipeline. The team must process change data from cloud object storage, filter out or isolate invalid records, and ensure the timely delivery of clean data to downstream consumers. The team is small, under tight deadlines, and wants to minimize operational overhead while keeping pipelines auditable and maintainable.
Which approach should the data engineer implement?

A) Implement ingestion using Auto Loader with Structured Streaming, and manage invalid data handling and table updates using checkpointing and merge logic.
B) Use a hybrid approach: Ingest with Auto Loader into Bronze tables, then process using SQL queries in Databricks Workflows to generate cleaned Silver and Gold tables on a schedule.
C) Use LDP to build declarative pipelines with Streaming Tables and Materialized Views, leveraging built-in support for data expectations and incremental processing.
D) Ingest data directly into Delta tables via Spark jobs, apply data quality filters using UDFs, and use LDP for creating Materialized Views.

2. Which statement regarding stream-static joins and static Delta tables is correct?

A) Each microbatch of a stream-static join will use the most recent version of the static Delta table as of each microbatch.
B) Each microbatch of a stream-static join will use the most recent version of the static Delta table as of the job's initialization.
C) The checkpoint directory will be used to track updates to the static Delta table.
D) The checkpoint directory will be used to track state information for the unique keys present in the join.
E) Stream-static joins cannot use static Delta tables because of consistency issues.

3. A departing platform owner currently holds ownership of multiple catalogs and controls storage credentials and external locations. A data engineer has been asked to ensure continuity: transfer catalog ownership to the platform team group, delegate ongoing privilege management, and retain the ability to receive and share data via Delta Sharing. Which role must be in place to perform these actions across the metastore?

A) Workspace Admin, because workspace admins can transfer ownership of any Unity Catalog object.
B) Catalog Owner, because catalog owners can transfer any object in any catalog in the metastore.
C) Metastore Admin, because metastore admins can transfer ownership and manage privileges across all metastore objects, including shares and recipients.
D) Account Admin, because account admins can only create metastores but cannot change ownership of catalogs.

4. 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) DESCRIBE HISTORY dev.pii test
C) SHOW TABLES dev
D) DESCRIBE EXTENDED dev.pii test
E) SHOW TBLPROPERTIES dev.pii test

5. A data engineer is attempting to execute the following PySpark code:
df = spark.read.table("sales")
result = df.groupBy("region").agg(sum("revenue"))
However, upon inspecting the execution plan and profiling the Spark job, they observe excessive data shuffling during the aggregation phase.
Which technique should be applied to reduce shuffling during the groupBy aggregation operation?

A) Caching the DataFrame df.
B) Use coalesce() after the aggregation.
C) Repartition by region before aggregation.
D) Use broadcast join.

Solutions: