How difficult is the Databricks Data Engineer Associate exam?

This is an Associate-level exam with 45 questions in 90 minutes, requiring approximately 70% to pass. It focuses on Lakehouse architecture, ELT development with Spark SQL and Python, Delta Lake core features, and Unity Catalog fundamentals. At least 6 months of hands-on Databricks experience is recommended.

How much does Delta Lake cover in the exam?

Delta Lake is a core topic, accounting for roughly 20-25% of questions. You need to master ACID transactions, Time Travel, OPTIMIZE and Z-ORDER commands, Schema Evolution, MERGE INTO syntax, and basic Delta Live Tables concepts.

What Spark programming knowledge is tested?

The exam primarily tests Spark SQL and PySpark DataFrame API, including reading/writing various data formats, data transformations using window functions and aggregations, Structured Streaming basics (trigger modes and watermarks), and Auto Loader for incremental data ingestion. Low-level Spark RDD APIs are not required.

What Unity Catalog topics are covered?

Unity Catalog questions focus on the three-level namespace (catalog.schema.table), data access control (GRANT/REVOKE), data lineage tracking, and sharing data across multiple Workspaces. Understanding the differences between Unity Catalog and the legacy Hive Metastore is also important.

Are Databricks Workflows heavily tested?

Yes, production pipeline orchestration is an important topic. You should understand how to create multi-task workflows with Databricks Jobs, task dependencies, scheduling strategies, failure retry mechanisms, and code deployment via Repos and CI/CD.

How should I prepare effectively for this certification?

Start with the official Databricks Data Engineering with Databricks learning path, then practice hands-on with Databricks Community Edition. Focus on Delta Lake operations, Structured Streaming, and Unity Catalog. Use our practice exams to familiarize yourself with question formats and identify knowledge gaps.

其他助理级📊 数据

Databricks Certified Data Engineer Associate

Databricks Certified Data Engineer Associate 认证验证 Lakehouse 架构、Delta Lake、Spark SQL ELT 开发、Databricks Workflows 编排与 Unity Catalog 数据治理能力。

Start Practice Browse Learning Path

Exam Fee

Questions

90m

Exam Duration

70/100

Passing Score

✓

Bottom line · Worth it

Lakehouse 架构正在取代传统数据仓库，这张证是进入 Databricks 生态的最快路径。

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What this certification covers

This page is structured for quick scanning first: exam format, fit, prep time, and the actual study scope.

Databricks Certified Data Engineer Associate 验证你在 Databricks Lakehouse 平台上构建和维护数据管道的能力。45 题，90 分钟，及格线约 70%，考试费 $200 USD，认证有效期 2 年。

考试 5 大域：数据摄取（30%）、数据处理与转换（31%）、生产化数据管道（18%）、数据治理（11%）和 Databricks 平台（10%）。数据摄取 + 处理加起来超过 60%，考的是 Auto Loader、COPY INTO、Delta Lake MERGE INTO、Structured Streaming 这些 Databricks 特有的工具链。

与 Databricks Data Engineer Professional 的区别：Associate 考"你会不会用这些工具"，Professional 考"给你一个复杂的多跳 ETL 管道场景，你怎么设计错误处理和数据质量检查"。

You will work with

Databricks LakehouseApache SparkDelta LakeETL PipelinesSQLPythonData Governance

After preparation

Pass the Databricks Data Engineer Associate certification exam with confidence
Master key concepts across all exam domains
Identify and strengthen weak areas before the exam

Exam details

Exam Code

Databricks DEA

Provider

其他认证机构

Duration

90 minutes

Question Count

65 questions

Passing Score

70/100

Validity

3 years

Exam Fee

$0 USD

Question Types

single-choice, multiple-choice

Languages

English

Official Page

Open AWS page

Who should take it

Good fit

数据工程师希望验证 Databricks Lakehouse 平台技能
ETL/ELT 开发人员转型到现代数据湖架构
使用 Apache Spark 和 Delta Lake 的数据专业人员
希望获得 Databricks 官方认证的数据平台工程师

Before you start

熟悉 SQL 和 Python 基础编程
了解数据工程概念（ETL、数据管道、数据仓库）
具备 Apache Spark 或 Databricks 平台基本使用经验

Is it worth it? Career value

Salary ranges, target job titles, and the real career impact of holding Databricks Data Engineer Associate.

澳洲

$120K-170KAUD

美国

$130K-190KUSD

新加坡

$100K-150KSGD

Data EngineerETL DeveloperAnalytics EngineerLakehouse Engineer

Databricks 的市场增长

Databricks 在 2024 年的 ARR（年度经常性收入）突破 $2.4B，同比增长 50%+。越来越多的企业从 Snowflake 或传统数据仓库迁移到 Databricks Lakehouse。数据工程岗位中提到"Databricks"的 JD 占比从 2022 年的 8% 增长到 2025 年的 22%（澳洲 Seek 数据）。

适合考的人：有 SQL 和 Python 基础、正在学习或使用 Spark 的数据工程师。考试可以选择 Spark SQL 或 PySpark 作答，选自己熟悉的。

不适合考的人：完全没用过 Databricks 平台的人。考试题目假设你知道 Databricks Workspace 的界面、Notebook 的基本操作、Cluster 的启动方式。建议先注册 Databricks Community Edition（免费）跑几个 Notebook。

Study preparation

With hands-on AWS

3-4 weeks

From scratch

6-8 weeks

Daily pace

1.5-2 hours/day

Learning path preview

3 chapters

Databricks Data Engineer Associate Exam Overview

40 min

Core Knowledge Review

120 min

Exam Preparation & Practice

100 min

Step-by-step preparation

A concrete week-by-week plan from past test-takers — not generic advice.

第一阶段：Delta Lake 基础（1-2 周）

Delta Lake 的 ACID 事务、Time Travel（VERSION AS OF / TIMESTAMP AS OF）、OPTIMIZE + Z-ORDER 文件压缩、VACUUM 清理旧版本文件。理解 Delta Lake 和普通 Parquet 的区别 — Delta 有事务日志（_delta_log）。

第二阶段：数据摄取 + ELT（2 周）

Auto Loader（cloudFiles 格式）vs COPY INTO 的选择：Auto Loader 适合持续增量摄取，COPY INTO 适合一次性批量加载。Structured Streaming 的 trigger 模式（processingTime/availableNow/once）。MERGE INTO 的 upsert 逻辑。

第三阶段：Workflows + Unity Catalog + 模考（1-2 周）

Databricks Workflows 的多任务 Job（Task Dependencies、Retry Policy）。Unity Catalog 的三层命名空间（catalog.schema.table）和 GRANT/REVOKE 权限模型。做 Databricks 官方 Practice Exam + 1-2 套第三方模考。

Real test-taker experiences

What it actually took for real candidates to pass — prep time, scores, and lessons learned.

有 Spark 经验的话 3 周够了。最容易出错的是 Auto Loader 和 COPY INTO 的区别题 — 记住 Auto Loader 用 checkpointLocation 跟踪已处理文件，COPY INTO 用内部状态。另外 MERGE INTO 的语法（WHEN MATCHED / WHEN NOT MATCHED）至少出了 3 题。

数据工程师 2 年通过

Melbourne Fintech · 3 weeks prep

没用过 Spark 的话比较吃力。PySpark DataFrame API 的题可以跳过选 Spark SQL 版本 — 但 Delta Live Tables 的声明式语法必须理解，考试出了好几题。

SQL 分析师转数据工程通过

· 7 weeks prep

Certification comparison

	Databricks Data Engineer Associate	Databricks Data Engineer Professional	Databricks DEA
Provider	其他	其他	其他
Level	助理级	专业级	助理级
Fee	$0	$0	$0
Duration	90 min	90 min	90 min
Question count	65	65	65
Validity	3 yrs	3 yrs	3 yrs

Study tips and common mistakes

💡

**选 SQL 还是 PySpark**：考试两种都出，但如果你更熟悉 SQL，大部分题都可以用 SQL 思维解答。

💡

**Delta Live Tables 声明式语法**：知道 @dlt.table 和 @dlt.view 的区别 — table 是物化的，view 是虚拟的。

💡

**45 题 90 分钟很充裕**：平均每题 2 分钟，大部分题不需要计算，认真读题即可。

⚠️

**Auto Loader vs COPY INTO 选错** — Auto Loader 自动发现新文件（基于 checkpointing），适合流式摄取；COPY INTO 需要手动触发，适合批量加载。题目说"每小时新增文件"选 Auto Loader。

⚠️

**VACUUM 的保留期** — 默认保留 7 天的历史版本，低于 7 天的 VACUUM 需要关闭安全检查（spark.databricks.delta.retentionDurationCheck.enabled = false）。考试会问"为什么 VACUUM 报错"。

⚠️

**Unity Catalog 权限继承** — Catalog 级别的 GRANT 自动继承到下面的 Schema 和 Table，但 Table 级别的 GRANT 不向上继承。

FAQ

Frequently Asked Questions

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