Skip to main content
CertificationsDatabricksDB-DEA-101
Databricks
Associate
DB-DEA-101

Databricks Certified Data Engineer Associate

1k+ Learners
4.75(2331 ratings)
Updated 8/18/2026
Databricks Certified Data Engineer Associate
Pro Mock
0Cheat Sheet(for Quick Exam Reference)
5Mock Tests20 Questions • 60 mins
6Practice Tests30 Questions • 90 mins
1Final Test51 Questions • 120 mins

Overview

The Databricks Certified Data Engineer Associate certification validates an individual's ability to perform foundational data engineering tasks using the Databricks Data Intelligence Platform. This includes understanding the Databricks workspace and architecture, performing ETL (Extract, Transform, Load) operations using Apache Spark SQL or PySpark, and orchestrating workloads with Databricks Workflows. Successful candidates can efficiently ingest, transform, and manage data pipelines in production environments using Databricks and its integrated tools.

Who Should Take This Course

Aspiring or junior data engineers using Databricks for ETL and pipeline development
Developers looking to validate skills in Apache Spark SQL and PySpark on Databricks
Professionals working on data ingestion, transformation, and workflow automation
Individuals aiming to pursue the Databricks Data Engineer Professional certification

Exam Details

Exam Code

Data Engineer Associate

Level

Associate

Duration

90 mins

Total Questions

45

Passing Score

Not specified

Fee (USD)

$200

Delivery

Online proctored

Languages

English, Japanese, Português BR, Korean

Negative Marking

No

Domain Distribution

Databricks Intelligence Platform

10%
Understand the Databricks workspace, architecture, and environmentExplain the Databricks Lakehouse and Delta Lake fundamentalsIdentify Databricks components and their roles (clusters, notebooks, jobs)Understand how Databricks integrates with cloud storage and compute layers

Development & Ingestion

30%
Use Apache Spark SQL and PySpark for data ingestion and ETLConnect and extract data from external sources (cloud storage, databases, APIs)Implement ingestion pipelines with Auto Loader or standard readsManage schema inference, data formats (Parquet, JSON, CSV), and metadata

Data Processing & Transformations

31%
Apply Spark transformations: filtering, joining, grouping, aggregationsUse User-Defined Functions (UDFs) for complex processingManage semi-structured and structured data (JSON, Delta Tables)Implement data cleaning, deduplication, and type conversionsLeverage caching and partitioning for performance optimization

Productionizing Data Pipelines

18%
Configure and schedule Databricks Workflows for automated jobsBuild, deploy, and monitor production pipelinesHandle job dependencies, retries, and notificationsImplement incremental processing and CDC (Change Data Capture)Use Delta Live Tables for pipeline orchestration and versioning

Data Governance & Quality

11%
Apply access control and permissions using Unity CatalogManage data lineage and audit trailsEnsure data quality through validations, expectations, and monitoringApply compliance best practices for secure data handling

Public Questions

Discussion

Every comment below is from a learner who has actually put in practice-exam time on this certification.

0/2000

Cheat Sheet

Quick Reference

Not Available

Build Your Package

Mock & CheatSheet Free
Total Price₹0

Build Your Custom Test

Set up a personalized quiz to target specific domains and identify weaknesses.

★

Have you taken this exam?

Share your experience and help other learners by writing a review.