Do I need the Databricks Data Engineer Associate before the Professional?

No. The Databricks Certified Data Engineer Professional exam has no required prerequisite. Databricks recommends about one year of hands-on data engineering experience and treats the Associate as a useful stepping stone, but it does not gate registration. You can sit the Professional exam directly, though most people pass the Associate first because the Professional assumes everything the Associate covers plus production-grade depth.

How many questions are on the Databricks Data Engineer Professional exam?

59 scored multiple-choice questions in 120 minutes, per the current exam guide effective July 3, 2026. Databricks may add a few unscored pilot questions with the time adjusted to match. That is about two minutes per question. Many older guides still say 60 questions and a six-domain outline; that is the pre-2026 version, so use material that matches the current 10-section guide.

What is the passing score for the Databricks Data Engineer Professional exam?

Databricks does not publish the passing score for the Data Engineer Professional exam. The often-repeated 70% figure is unofficial and is not stated in the exam guide, so do not treat it as confirmed. Aim to answer practice sets comfortably and consistently rather than targeting a specific percentage, because the real threshold is not disclosed.

How much does the Databricks Data Engineer Professional exam cost?

US$200 plus applicable tax per attempt. There is no free retake; each attempt is the full fee. The exam is delivered online with a proctor or at a test center, in English. Given the cost per attempt, it pays to drill practice questions until you are consistently clearing the material before you book.

What is the difference between the Databricks Data Engineer Associate and Professional?

The Associate certifies foundational data engineering on Databricks: the Lakehouse, basic ELT with Spark SQL and Python, and simple pipelines and governance. The Professional certifies production-grade work: advanced streaming, cost and performance optimization, security and governance depth, testing, and CI/CD deployment with declarative bundles and Git folders. The Associate is recommended preparation but not required for the Professional.

What does the Databricks Data Engineer Professional exam cover?

The current July 2026 guide lists ten sections: developing code with Python and SQL, data ingestion and acquisition, data transformation and quality, data sharing and federation, monitoring and alerting, cost and performance optimization, security and compliance, data governance, debugging and deploying, and data modeling. It tests Delta Lake, Unity Catalog, Auto Loader, Lakeflow declarative pipelines and jobs, Structured Streaming, and CI/CD, all as production scenarios.

Is the Databricks Data Engineer Professional certification worth it?

For a working data engineer on Databricks, yes. It signals that you can build, secure, optimize, and deploy production pipelines, not just prototype them, and it carries weight in hiring for senior data engineering roles. If you are newer to Databricks, start with the Associate to build the foundation the Professional assumes, then move up once you run real production workloads.

Databricks Certified Data Engineer Professional

Databricks Data Engineer Professional Practice Exam: Certification Practice Questions

Upload your Databricks study notes, pipeline runbooks, or course slides, and the AI writes unlimited Data Engineer Professional practice questions with an answer key in seconds. Built for the current exam updated July 3, 2026 (59 questions, 120 minutes) and the production pipeline scenarios Databricks actually tests, including Lakeflow, Delta Lake, and Unity Catalog.

Your study files are processed securely and deleted automatically after your practice questions are built.

Upload your Databricks notes and generate your first question set

Click to upload or drag and drop

PDF, DOCX, PPTX, TXT, JPG, JPEG, PNG, HEIC, ODP, ODT, BMP, or TIFF

up to 20MB

Please wait, your quiz is being created...

Uploading...

The Databricks Certified Data Engineer Professional exam is 59 scored multiple-choice questions in 120 minutes, it costs US$200, and it has no required prerequisite. Databricks does not publish the passing score. The exam was restructured effective July 3, 2026 into ten sections covering code development in Python and SQL, ingestion, transformation and quality, monitoring, cost and performance optimization, security, governance, deployment, and data modeling, using current tools like Lakeflow declarative pipelines, Delta Lake, and Unity Catalog. The credential is valid for two years.

Last updated July 2026

Study the July 2026 version, and mind the renamed tools

The name of this certification has not changed, but the exam has. The current exam guide is effective July 3, 2026 and replaced the older blueprint with a new 10-section outline and 59 scored questions. The previous version had six domains and 60 questions, and most practice material online still describes that older structure. If your prep lists six domains, treat it as out of date and confirm it maps to the current ten sections before you rely on it.

The update also renamed several tools you will see in the questions. Delta Live Tables is now Lakeflow Spark Declarative Pipelines, Databricks Asset Bundles are now Declarative Automation Bundles, Repos are now Git folders, and APPLY CHANGES is now the AUTO CDC APIs. The underlying concepts are the same, but the exam uses the current names, so make sure your study notes and question sets do too.

What the Databricks Data Engineer Professional exam tests

The current exam guide lists ten sections. Databricks publishes the section names in the July 2026 guide; the approximate weights below come from the Databricks certification page and give you a sense of where the points sit. Confirm the exact figures on the official exam guide before you plan study time. What is clear is that developing code, cost and performance tuning, and transformation together carry the most weight, and every section is tested as a production scenario.

Section	Approx. weight	What is actually in it
Developing Code with Python and SQL	22%	PySpark and SQL, window functions, joins, and UDFs. The single largest section: the exam expects you to read and reason about real code, not just recognize syntax.
Cost and Performance Optimization	13%	Liquid clustering, deletion vectors, data skipping, compute sizing including serverless, and tuning jobs to be fast without wasting spend. This is where the Professional goes well beyond the Associate.
Data Transformation, Cleansing, and Quality	10%	Building reliable transformations, enforcing data quality expectations, and the Medallion architecture from bronze to gold.
Monitoring and Alerting	10%	System tables, the Spark UI, the Query Profiler, and setting up alerts so pipeline failures and drift surface before users notice.
Ensuring Data Security and Compliance	10%	Row filters and column masks, PII masking and anonymization, and securing data across a Unity Catalog governed workspace.
Debugging and Deploying	10%	Unit and integration testing, CI/CD with Declarative Automation Bundles and Git folders, and the Databricks CLI and REST API.
Data Ingestion and Acquisition	7%	Auto Loader, Lakeflow declarative pipelines and jobs, and streaming and batch ingestion patterns.
Data Governance	7%	Unity Catalog structure, lineage, and managing access to catalogs, schemas, and tables at scale.
Data Modeling	6%	Modeling for the Lakehouse, change data feed and AUTO CDC, and designing tables that stay maintainable.
Data Sharing and Federation	5%	Delta Sharing and querying federated sources, sharing data securely without copying it.

Because every section is scenario-based, the fastest way to prepare is to practice choosing production designs, not memorizing features. Generate practice questions from your own Databricks notes across all ten sections, and lean into the code, cost, and streaming decisions that working data engineers make on real Databricks projects.

Exam fee: US$200
Format: 59 Q / 120 min
Passing score: Not published
Prerequisite: None required

Why drill questions for Databricks Data Engineer Professional?

Because the exam rewards production judgment, and judgment is built by repetition on realistic pipeline scenarios. A question does not ask what Auto Loader is; it describes files landing continuously and asks how to ingest them exactly once, keep the job cheap, and alert on failures. You can build on Databricks every day and still miss these if your work has only ever used one pattern. Practice questions that force the production decision are the fastest way to widen that range before you sit a US$200 exam with no free retake.

Where candidates lose points

Reading real PySpark and SQL under time pressure, cost and performance tuning, and CI/CD deployment with bundles and Git folders. Engineers who only build prototypes underestimate the security, testing, and deployment sections. Drill code and cost hardest, because together they are the heaviest part of the exam.

Match the current format

Generate questions that use the current Lakeflow names and read like the exam: a requirement, a constraint, and several plausible designs where only one is best. That trains you to eliminate the answer that works but wastes compute or skips governance, which is exactly the discrimination the Professional tests.

Uploading your notes and generating questions from them is cheap insurance on an exam that costs US$200 per attempt and expects real production experience. It forces you across all ten sections and the current tool names, rather than practicing only the part of Databricks your current project happens to use.

Associate or Professional: which Databricks data engineer exam?

Databricks has two data engineering certifications. The Associate is the foundation; the Professional is the advanced tier above it. Neither gates the other, so you can technically take the Professional first, but most people build the base with the Associate because the Professional assumes it. Here is how they compare so you pick the right starting point.

	Data Engineer Associate	Data Engineer Professional
Level	Foundational	Advanced, production-focused
Cost	US$200	US$200
Prerequisite	None	None (Associate recommended)
Focus	Lakehouse basics, ELT, simple pipelines	Streaming, cost tuning, security, CI/CD
Valid for	2 years	2 years
Best for	New to Databricks engineering	Running production pipelines

Newer to Databricks? Start with the Databricks Data Engineer Associate practice exam to build the foundation the Professional assumes. If you also work in Snowflake, the SnowPro Advanced Data Engineer practice exam is a related data-platform credential many engineers compare alongside it.

How to build Databricks Data Engineer Professional practice questions that match the exam

The exam tests production judgment across ten sections. Your questions should drill exactly that.

1 Upload current material: Feed in notes built on the July 2026 ten-section guide and the current Lakeflow tool names, not a six-domain outline. Confirm the sections on Databricks' official guide so your questions match the real exam.
2 Practice as scenarios: Generate questions that give a requirement and several plausible pipeline designs. That trains the elimination skill the exam tests, where more than one answer works but only one is the best production build.
3 Weight code and cost: Put extra practice on reading PySpark and SQL, cost and performance tuning, and CI/CD deployment. Code development and cost optimization are the two heaviest sections, so they deserve the most reps.
4 Retake until it clicks: Regenerate fresh sets and retake until the best production design comes back instantly. Because Databricks does not publish the passing score, aim to clear practice sets comfortably before you book.

Databricks Data Engineer Professional exam questions, answered

Do I need the Associate before the Professional?: No. The Data Engineer Professional exam has no required prerequisite. Databricks recommends about a year of hands-on data engineering experience and treats the Associate as a useful stepping stone, but it does not gate registration. You can sit the Professional directly, though most people pass the Associate first because the Professional assumes everything it covers plus production-grade depth.
How many questions are on the exam?: 59 scored multiple-choice questions in 120 minutes, per the exam guide effective July 3, 2026. A few unscored pilot questions may be added with the time adjusted. Many older guides still say 60 questions and six domains; that is the pre-2026 version. Use material that matches the current ten-section guide.
What is the passing score?: Databricks does not publish it. The 70% figure you will see repeated is unofficial and does not appear in the exam guide, so do not treat it as confirmed. Because the real threshold is not disclosed, aim to answer practice sets comfortably and consistently rather than targeting a specific number.
How much does it cost?: US$200 plus applicable tax per attempt, with no free retake. It is delivered online with a proctor or at a test center, in English. When your two-year cycle comes up, you renew by passing the then-current version of the exam. Given the cost per attempt, it pays to drill until you are consistently passing practice sets first.
What is the difference between the Associate and Professional?: The Associate certifies foundational data engineering on Databricks: the Lakehouse, basic ELT with Spark SQL and Python, and simple pipelines and governance. The Professional certifies production-grade work: advanced streaming, cost and performance optimization, security and governance depth, testing, and CI/CD deployment. The Associate is recommended preparation but not required for the Professional.
What tools and terms changed in the July 2026 update?: Delta Live Tables became Lakeflow Spark Declarative Pipelines, Databricks Asset Bundles became Declarative Automation Bundles, Repos became Git folders, and APPLY CHANGES became the AUTO CDC APIs. The concepts are the same, but the exam uses the current names, so make sure your notes and question sets use them too.
Is the Databricks Data Engineer Professional worth it?: For a working data engineer on Databricks, yes. It signals that you can build, secure, optimize, and deploy production pipelines, not just prototype them, and it carries real weight in hiring for senior data engineering roles. If you are newer to Databricks, start with the Associate to build the foundation the Professional assumes, then move up once you run real production workloads.

PDFQuiz is not affiliated with, endorsed by, or sponsored by Databricks. Databricks and Lakeflow are trademarks of Databricks, Inc. This generator builds practice questions from material you upload and is a study aid, not a substitute for the official exam guide or training. Exam details change, so always confirm current details on Databricks' certification page before you book.

Related study tools

Building your Databricks path? The Databricks Data Engineer Associate practice exam is the foundation to clear first. Work in Snowflake too? The SnowPro Advanced Data Engineer practice exam and the SnowPro Core practice exam are related data-platform credentials. Any study guide works with the certification exam generator, or start from any PDF with the PDF to practice test generator.

Build your first Databricks Data Engineer Professional practice set

Upload your Databricks notes or the current exam guide and generate code, cost, streaming, and deployment practice questions with an answer key in under a minute.

Start Creating Practice Questions