Exam Name: Databricks Certified Data Engineer Associate Exam
Certification Provider: Databricks
Corresponding Certification: Databricks Certification
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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Pipeline Architecture | 15-20% | - Design data pipelines for batch and streaming - Implement incremental data processing - Monitor and optimize pipeline performance - Understand ELT vs ETL patterns |
| Spark SQL and DataFrames | 15-20% | - Join and union DataFrames - Handle null values and data quality - Aggregate and group data - Write and execute Spark SQL queries |
| Lakehouse Platform Concepts | 10-15% | - Understand the Lakehouse architecture and its benefits - Explain data governance and security concepts - Describe key Databricks Lakehouse platform components |
| Apache Spark Data Processing Fundamentals | 20-25% | - Create and use Spark DataFrames - Work with structured data types (arrays, maps, structs) - Use Spark SQL for data processing - Apply transformations and actions on DataFrames |
| Python for Data Engineering | 10-15% | - Use PySpark for data processing - Implement user-defined functions (UDFs) - Work with Spark APIs in Python |
| Delta Lake Fundamentals | 20-25% | - Understand ACID transactions and time travel - Write to and read from Delta tables - Create and manage Delta tables - Explain Delta Lake features and benefits |
Databricks-Certified-Data-Engineer-Associate Exam FAQ for IT Career Starters
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$200 USD per attempt, 70% to pass. Retakes bill the full fee again — which is why accurate preparation with the 322 practice questions from Lead1Pass is the economical route.
Yes — a free Databricks Certified Data Engineer Associate demo is available to download before you decide. Evaluate the questions and answers yourself; every purchase then includes 365 days of free updates, renewable at 50% off afterward.
90 minutes for 60 questions. Practice seriously with the clock running — timed sessions in the Lead1Pass engine turn time pressure into routine before test day.
The Databricks Certified Data Engineer Associate is Databricks's certification exam for Databricks Certification, at the Associate level. For IT workers with aspirations, it's essential proof of capability — the line that starts or advances a career. Related credentials include Databricks Certified Data Analyst Associate.
The Databricks Certified Data Engineer Associate blueprint spans 6 domains — including Spark SQL and DataFrames (15-20%), Apache Spark Data Processing Fundamentals (20-25%), Data Pipeline Architecture (15-20%). Allocate study time by weighting, and consult the full outline above for every subtopic.
Recommended: 6+ months of experience with Databricks and Apache Spark Vendors revise eligibility rules periodically, so confirm the current requirements on the official page (official Databricks-Certified-Data-Engineer-Associate exam page) before registering.
Databricks Certified Data Engineer Associate Sample Questions:
A single Job runs two notebooks as two separate tasks. A data engineer has noticed that one of the notebooks is running slowly in the Job's current run. The data engineer asks a tech lead for help in identifying why this might be the case.
Which of the following approaches can the tech lead use to identify why the notebook is running slowly as part of the Job?
- A. They can navigate to the Tasks tab in the Jobs UI and click on the active run to review the processing notebook.
- B. They can navigate to the Runs tab in the Jobs UI to immediately review the processing notebook.
- C. There is no way to determine why a Job task is running slowly.
- D. They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.
- E. They can navigate to the Tasks tab in the Jobs UI to immediately review the processing notebook.
Correct Answer: D 🗳️
A data engineer is designing a cost-optimized, event-driven pipeline. They configure a Lakeflow Job with a File Arrival trigger to watch an S3 bucket. The job runs a notebook that uses Auto Loader with trigger(availableNow=True) to ingest data into a Bronze table. What is the technical relationship between the File Arrival trigger and Auto Loader in this integration pattern?
- A. Using a File Arrival trigger requires the engineer to disable Auto Loader's checkpointing to prevent the job from processing the same file multiple times.
- B. The File Arrival trigger starts the job run, while Auto Loader uses its internal checkpoint to independently identify and process only the new files that have arrived since the last successful commit.
- C. Auto Loader must be configured in File Notification mode to work with a Lakeflow Job File Arrival trigger.
- D. The File Arrival trigger automatically passes the specific file path of the new arrival to Auto Loader, allowing the engineer to skip the source path configuration in the code.
Correct Answer: B 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
A pipeline uses COPY INTO to ingest CSV files from cloud object storage into a Unity Catalog Delta table. Some files are occasionally re-uploaded with corrections using the same filename.
The engineer needs the corrected data ingested as soon as it occurs. What should the engineer do?
- A. Overwrite the target Delta table on each run
- B. Reload all files from the source path on each run
- C. Load corrections as new files and apply updates to the target table
- D. Recreate the target table before each run
Correct Answer: C 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
In which of the following scenarios should a data engineer select a Task in the Depends On field of a new Databricks Job Task?
- A. When another task needs to use as little compute resources as possible
- B. When another task needs to successfully complete before the new task begins
- C. When another task has the same dependency libraries as the new task
- D. When another task needs to fail before the new task begins
- E. When another task needs to be replaced by the new task
Correct Answer: B 🗳️
A data engineer must support self-serve BI dashboards for hundreds of business users who run ad hoc, high-concurrency SQL queries throughout the day against governed Unity Catalog tables.
The team needs a near-instant start, autoscaling without manual tuning, and the best performance for SQL while minimizing operational overhead. Which Databricks compute should the data engineer use?
- A. SQL Warehouse (Serverless) with Photon enabled.
- B. SQL Warehouse (Classic) with a fixed cluster size.
- C. Jobs compute clusters triggered by dashboards on a schedule.
- D. All-purpose classic cluster with manual autoscaling enabled.
Correct Answer: A 🗳️
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