Understand the certification
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"。
Exam at a glance
- Exam code
- Databricks DEA
- Provider
- 其他
- Format
- single-choice / multiple-choice
- Language
- English
- Validity
- 3 years
Skills in focus
Learning outcomes
- 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
Who this is for
- 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
Your learning path
3 chapters
Plan your preparation
- Learning hours
- 26h
- With relevant experience
- 3-4 weeks
- Starting from scratch
- 6-8 weeks
- Daily study
- 1.5-2h
Included in your preparation
- 250 practice questions with detailed explanations
- Mock exams simulating real test conditions
- AI-powered tutoring for personalized study
- Progress tracking and weak area identification
1. 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)。
2. 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。
3. 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。
Career value
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。
- 澳洲
- AUD 120,000 – 170,000
- 美国
- USD 130,000 – 190,000
- 新加坡
- SGD 100,000 – 150,000
Preparation tips
- **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。
Common mistakes
- **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。
Before you register
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.
Learner experiences
Loading reviews…
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
Melbourne Fintech · 通过 · 3 weeks
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
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