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DatabricksAdvancedDatabricksData EngineeringData PipelinesLakehouse

Databricks Certified Data Engineer Professional

DATA-ENGINEER-PROFESSIONAL

The Databricks Certified Data Engineer Professional exam validates advanced data engineering skills on the Databricks Data Intelligence Platform. Practice with scenario-based questions covering production pipelines, data processing, testing, deployment, monitoring, performance optimization, security, and governance.

Take a timed, 60-question mock exam that simulates the real test — or browse every question with answers and explanations at your own pace.

Questions

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  1. 1An 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?
  2. 2The 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.
  3. 3The 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?
  4. 4A Delta table of weather records is partitioned by date and has the below schema: date DATE, device_id INT, temp FLOAT, latitude FLOAT, longitude FLOAT To find all the records from within the Arctic Circle, you execute a query with the below filter: latitude > 66.3 Which statement describes how the Delta engine identifies which files to load?
  5. 5The data engineering team has configured a job to process customer requests to be forgotten (have their data deleted). All user data that needs to be deleted is stored in Delta Lake tables using default table settings. The team has decided to process all deletions from the previous week as a batch job at 1am each Sunday. The total duration of this job is less than one hour. Every Monday at 3am, a batch job executes a series of VACUUM commands on all Delta Lake tables throughout the organization. The compliance officer has recently learned about Delta Lake's time travel functionality. They are concerned that this might allow continued access to deleted data. Assuming all delete logic is correctly implemented, which statement correctly addresses this concern?
  6. 6A junior data engineer has configured a workload that posts the following JSON to the Databricks REST API endpoint 2.0/jobs/create. Assuming that all configurations and referenced resources are available, which statement describes the result of executing this workload three times?
  7. 7An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the field pk_id. For auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour. Which solution meets these requirements?
  8. 8A table in the Lakehouse named customer_churn_params is used in churn prediction by the machine learning team. The table contains information about customers derived from a number of upstream sources. Currently, the data engineering team populates this table nightly by overwriting the table with the current valid values derived from upstream data sources. The churn prediction model used by the ML team is fairly stable in production. The team is only interested in making predictions on records that have changed in the past 24 hours. Which approach would simplify the identification of these changed records?
  9. 9A table is registered with the following code: Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders?
  10. 10A production workload incrementally applies updates from an external Change Data Capture feed to a Delta Lake table as an always-on Structured Stream job. When data was initially migrated for this table, OPTIMIZE was executed and most data files were resized to 1 GB. Auto Optimize and Auto Compaction were both turned on for the streaming production job. Recent review of data files shows that most data files are under 64 MB, although each partition in the table contains at least 1 GB of data and the total table size is over 10 TB. Which of the following likely explains these smaller file sizes?