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Databricks Databricks-Certified-Data-Engineer-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Data-Engineer-Associate
Exam Name:
Databricks Certified Data Engineer Associate Exam
Certification:
Databricks Certification
Vendor:
Databricks
Questions:
230
Last Updated:
Oct 13, 2026
Exam Status:
Stable
Databricks Databricks-Certified-Data-Engineer-Associate

Databricks-Certified-Data-Engineer-Associate: Databricks Certification Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Data Engineer Associate Exam Questions and Answers

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Question 1

A data engineer has finished developing a new Declarative Automation Bundle, formerly known as a Databricks Asset Bundle, for a streaming pipeline. The engineer must verify that the configuration is syntactically correct, deploy the code to the workspace, and finally trigger the pipeline to confirm that it runs as expected.

Which sequence of Databricks CLI commands performs these steps in the correct order?

Options:

A.

databricks bundle init → databricks bundle deploy → databricks bundle run

B.

databricks bundle validate → databricks bundle deploy → databricks bundle run

C.

databricks bundle validate → databricks bundle sync → databricks bundle execute

D.

databricks bundle check → databricks bundle upload → databricks bundle start

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Question 2

A data engineer streams customer orders into a Kafka topic (orders_topic) and is currently writing the ingestion script of a DLT pipeline. The data engineer needs to ingest the data from Kafka brokers to DLT using Databricks

What is the correct code for ingesting the data?

A)

B)

C)

D)

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 3

A data engineer is maintaining an ETL pipeline code with a GitHub repository linked to their Databricks account. The data engineer wants to deploy the ETL pipeline to production as a databricks workflow.

Which approach should the data engineer use?

Options:

A.

Databricks Asset Bundles (DAB) + GitHub Integration

B.

Maintain workflow_config.j son and deploy it using Databricks CLI

C.

Manually create and manage the workflow in Ul

D.

Maintain workflow_conf ig. json and deploy it using Terraform

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