DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE Real Exam Questions
Databricks Certified Data Engineer Associate. Everything you need to prepare, practice, and pass.
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Certification Overview
The exam emphasizes the complete data engineer workflow on Databricks: ingesting raw data via Auto Loader or Spark, transforming with Spark SQL and Python using ELT (not ETL), managing data quality with Delta Lake features, monitoring jobs and data freshness, and deploying solutions with proper access control. The Lakehouse approach—combining structured and unstructured data in Delta—is the conceptual spine.
What This Certification Proves
This certification validates hands-on expertise in building data engineering solutions on the Databricks Lakehouse Platform, focusing on ELT workflows, Delta Lake management, and Spark SQL/Python development. It demonstrates proficiency in modern data engineering practices and is widely recognized as an entry-to-intermediate credential for data engineers working with Databricks.
Who Should Take This Exam
Data engineers with 1-3 years of experience, SQL developers transitioning to Spark, and cloud data professionals looking to formalize Databricks expertise. Ideal for those already working with Spark or considering migration to Databricks. Not beginner-level—assumes comfort with SQL and basic Python.
Topic Breakdown
5 domains covering 83 questions
| Domain | Questions | Weight |
|---|---|---|
| Elt With Spark Sql And Python | 28 | 34% |
| Databricks Lakehouse Platform | 21 | 25% |
| Data Management | 15 | 18% |
| Deployment And Operations | 12 | 14% |
| Monitoring And Logging | 7 | 8% |
Study Plans
Choose a study plan that matches your schedule and experience level
30 Days
Intensive Sprint
Week 1-2
- Master fundamentals: Elt With Spark Sql And Python
- Read Databricks official documentation
- Complete 3 questions daily
Week 3
- Deep dive: Databricks Lakehouse Platform
- Review weak areas from results
- Take 2 full-length exams
Week 4
- Review all flagged questions
- Timed exams to build stamina
- Final revision of key concepts
60 Days
Balanced Approach
Week 1-2
- Survey all exam domains
- Set up study environment
- Begin with foundational topics
Week 3-4
- Focus: Elt With Spark Sql And Python
- Focus: Databricks Lakehouse Platform
- 2 questions daily
Week 5-6
- Focus: Data Management
- Hands-on labs if applicable
- Review explanations for wrong answers
Week 7-8
- Complete all 83 questions
- Identify and eliminate weak areas
- Take 3 full-length timed tests
90 Days
Comprehensive Study
Month 1
- Learn all exam domains at a comfortable pace
- Build strong foundational knowledge
- 1 questions daily
Month 2
- Deep dive into each domain
- Hands-on practice and labs
- Take weekly timed exams
Month 3
- Work through all 83 questions
- Identify and eliminate weak areas
- Take 3 full-length timed exams
DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE-Specific Tips
- Master Delta Lake fundamentals first—ACID transactions, time travel, and schema evolution appear across multiple domains
- Focus heavily on Spark SQL and DataFrame APIs; use official Databricks documentation and hands-on notebook labs, not just practice questions
- Understand the medallion architecture (bronze/silver/gold) as it connects data management, ELT patterns, and real-world workflows
- Practice Auto Loader and Structured Streaming with actual Delta tables; these are tested in depth and require execution experience
- Study Databricks Jobs and access control (SQL, data, cluster-level) as they appear in deployment and monitoring sections
- Review Delta Live Tables syntax and best practices—this is a modern-first topic emphasized in newer exam versions
- Set up a free Databricks Community Edition workspace and complete 3-4 mini-projects covering ingestion→transformation→access before exam day
Relevant Career Roles
Sample Questions
Try 5 free questions from the DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE question bank
A data engineer has joined an existing project and they see the following query in the project repository: CREATE STREAMING LIVE TABLE loyal_customers AS SELECT customer_id - FROM STREAM(LIVE.customers) WHERE loyalty_level = 'high'; Which of the following describes why the STREAM function is included in the query?
A data engineer is running code in a Databricks Repo that is cloned from a central Git repository. A colleague of the data engineer informs them that changes have been made and synced to the central Git repository. The data engineer now needs to sync their Databricks Repo to get the changes from the central Git repository. Which of the following Git operations does the data engineer need to run to accomplish this task?
A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables. Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table. The cade block used by the data engineer is below: If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?
An engineering manager wants to monitor the performance of a recent project using a Databricks SQL query. For the first week following the project's release, the manager wants the query results to be updated every minute. However, the manager is concerned that the compute resources used for the query will be left running and cost the organization a lot of money beyond the first week of the project's release. Which of the following approaches can the engineering team use to ensure the query does not cost the organization any money beyond the first week of the project's release?
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