Databricks Certified Data Engineer Professional Sample Questions:

1. A transactions table has been liquid clustered on the columns product_id, user_id, and event_date. Which operation lacks support for cluster on write?

A) INSERT INTO operations
B) spark.writestream.format('delta').mode('append')
C) spark.write.format('delta').mode('append')
D) CTAS and RTAS statements

2. A data engineer is creating a daily reporting job. There are two reporting notebooks--one for weekdays and one for weekends. An "if/else condition" task is configured as
{{job.start_time.is_weekday}} == true to route the job to either the weekday or weekend notebook tasks. The same job would be used across multiple time zones. Which action should a senior data engineer take upon reviewing the job to merge or reject the pull request?

A) Reject, as the {{job.start_time.is_weekday}} is not a valid value reference.
B) Reject, as the {{job.start_time.is_weekday}} is for the UTC timezone.
C) Merge, as the job configuration looks good.
D) Reject, as they should use {{job.trigger_time.is_weekday}} instead.

3. The data engineer team is configuring environment for development testing, and production before beginning migration on a new data pipeline. The team requires extensive testing on both the code and data resulting from code execution, and the team want to develop and test against similar production data as possible.
A junior data engineer suggests that production data can be mounted to the development testing environments, allowing pre production code to execute against production data. Because all users have Admin privileges in the development environment, the junior data engineer has offered to configure permissions and mount this data for the team.
Which statement captures best practices for this situation?

A) Because access to production data will always be verified using passthrough credentials it is safe to mount data to any Databricks development environment.
B) Because delta Lake versions all data and supports time travel, it is not possible for user error or malicious actors to permanently delete production data, as such it is generally safe to mount production data anywhere.
C) In environments where interactive code will be executed, production data should only be accessible with read permissions; creating isolated databases for each environment further reduces risks.
D) All developer, testing and production code and data should exist in a single unified workspace; creating separate environments for testing and development further reduces risks.

4. A facilities-monitoring team is building a near-real-time PowerBI dashboard off the Delta table device_readings:
Columns:
device_id (STRING, unique sensor ID)
event_ts (TIMESTAMP, ingestion timestamp UTC)
temperature_c (DOUBLE, temperature in °C)
Requirement:
For each sensor, generate one row per non-overlapping 5-minute
interval, offset by 2 minutes (e.g., 00:02-00:07, 00:07-00:12, ...).
Each row must include interval start, interval end, and average
temperature in that slice.
Downstream BI tools (e.g., Power BI) must use the interval timestamps
to plot time-series bars.

A) WITH buckets AS (
SELECT device_id,
window(event_ts, '5 minutes', '2 minutes', '5 minutes') AS win,
temperature_c
FROM device_readings
)
SELECT device_id,
win.start AS bucket_start,
win.end AS bucket_end,
AVG(temperature_c) AS avg_temp_5m
FROM buckets
GROUP BY device_id, win
ORDER BY device_id, bucket_start;
B) SELECT device_id,
event_ts,
AVG(temperature_c) OVER (
PARTITION BY device_id
ORDER BY event_ts
RANGE BETWEEN INTERVAL 5 MINUTES PRECEDING AND CURRENT ROW
) AS avg_temp_5m
FROM device_readings
WINDOW w AS (window(event_ts, '5 minutes', '2 minutes'));
C) SELECT device_id,
window.start AS bucket_start,
window.end AS bucket_end,
AVG(temperature_c) AS avg_temp_5m
FROM device_readings
GROUP BY device_id, window(event_ts, '5 minutes', '5 minutes', '2 minutes') ORDER BY device_id, bucket_start;
D) SELECT device_id,
date_trunc('minute', event_ts - INTERVAL 2 MINUTES) + INTERVAL 2 MINUTES AS bucket_start, date_trunc('minute', event_ts - INTERVAL 2 MINUTES) + INTERVAL 7 MINUTES AS bucket_end, AVG(temperature_c) AS avg_temp_5m FROM device_readings GROUP BY device_id, date_trunc('minute', event_ts - INTERVAL 2 MINUTES) ORDER BY device_id, bucket_start;

5. A data engineer has created a new cluster using shared access mode with default configurations.
The data engineer needs to allow the development team access to view the driver logs if needed.
What are the minimal cluster permissions that allow the development team to accomplish this?

A) CAN RESTART
B) CAN ATTACH TO
C) CAN MANAGE
D) CAN VIEW

Solutions: