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Databricks (Databricks Certified Data Engineer Professional) Exam Questions PDF

Databricks Certified Data Engineer Professional pdf

Exam Code: Databricks Certified Data Engineer Professional
Exam Name: Databricks Certified Data Engineer Professional
Updated: Sep 28, 2026
202 Questions and Answers
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Exam Code: Databricks Certified Data Engineer Professional
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Exam Code: Databricks Certified Data Engineer Professional
Exam Name: Databricks Certified Data Engineer Professional
Updated: Sep 28, 2026
202 Questions and Answers
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Databricks Databricks Certified Data Engineer Professional Exam Questions

Databricks Certified Data Engineer Professional exams.

Question — (Single Choice)

An upstream system has been configured to pass the date for a given batch of data to the Databricks Jobs API as a parameter. The notebook to be scheduled will use this parameter to load data with the following code df = spark.read.format("parquet").load(f"/mnt/source/(date)") Which code block should be used to create the date Python variable used in the above code block?

Choose the answer:

A date = spark.conf.get("date")
B input_dict = input() date= input_dict["date"]
C import sys date = sys.argv[1]
D date = dbutils.notebooks.getParam("date")
E dbutils.widgets.text("date", "null") date = dbutils.widgets.get("date")

Question — (Single Choice)

The Databricks workspace administrator has configured interactive clusters for each of the data engineering groups. To control costs, clusters are set to terminate after 30 minutes of inactivity. Each user should be able to execute workloads against their assigned clusters at any time of the day. Assuming users have been added to a workspace but not granted any permissions, which of the following describes the minimal permissions a user would need to start and attach to an already configured cluster.

Choose the answer:

A "Can Manage" privileges on the required cluster
B Workspace Admin privileges, cluster creation allowed. "Can Attach To" privileges on the required cluster
C Cluster creation allowed. "Can Attach To" privileges on the required cluster
D "Can Restart" privileges on the required cluster
E Cluster creation allowed. "Can Restart" privileges on the required cluster

Question — (Single Choice)

When scheduling Structured Streaming jobs for production, which configuration automatically recovers from query failures and keeps costs low?

Choose the answer:

A Cluster New Job Cluster; Retries Unlimited; Maximum Concurrent Runs Unlimited
B Cluster New Job Cluster; Retries None; Maximum Concurrent Runs 1
C Cluster Existing All - Purpose Cluster; Retries Unlimited; Maximum Concurrent Runs 1
D Cluster Existing All - Purpose Cluster; Retries Unlimited; Maximum Concurrent Runs 1
E Cluster Existing All - Purpose Cluster; Retries None; Maximum Concurrent Runs 1

Question — (Single Choice)

The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. The recent_sensor_recordings table contains an identifying sensor_id alongside the timestamp and temperature for the most recent 5 minutes of recordings. The below query is used to create the alert The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger when mean (temperature) > 120. Notifications are triggered to be sent at most every 1 minute. If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?

Choose the answer:

A The total average temperature across all sensors exceeded 120 on three consecutive executions of the query
B The recent_sensor_recordingstable was unresponsive for three consecutive runs of the query
C The source query failed to update properly for three consecutive minutes and then restarted
D The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query
E The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query

Question — (Single Choice)

A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch named dev - 2.3.9 is not available from the branch selection dropdown. Which approach will allow this developer to review the current logic for this notebook?

Choose the answer:

A Use Repos to make a pull request use the Databricks REST API to update the current branch to dev - 2.3.9
B Use Repos to pull changes from the remote Git repository and select the dev - 2.3.9 branch.
C Use Repos to checkout the dev - 2.3.9 branch and auto - resolve conflicts with the current branch
D Merge all changes back to the main branch in the remote Git repository and clone the repo again
E Use Repos to merge the current branch and the dev - 2.3.9 branch, then make a pull request to sync with the remote repository

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