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Databricks Certified Data Engineer Professional (Data Engineer Professional) practice exam and study path

A free, timed 60-question Data Engineer Professional practice exam in 120 minutes, scored by domain, with every option explained after you submit. Also 240 practice questions you can check one at a time, a page for every task in the exam guide, and a study path. No sign-up.

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Data Engineer Professional exam pack:

$11.99for 12 months

The advanced Databricks data engineering exam: production pipelines in Python and SQL with Lakeflow pipelines, Structured Streaming and Lakeflow Jobs, CDC and sharing, monitoring with system tables and alerts, Delta Lake cost and performance tuning, security and compliance in Unity Catalog, debugging and deploying with bundles and Git folders, and data modeling.

The exam

Exam code
Data Engineer Professional
Questions
Not yet published
Time
120 minutes
Passing score
Not published
Exam fee
$200 (USD)
Question types
multiple choice, multiple response

60 scored multiple-choice questions in 120 minutes (unscored questions may be included and are not identified; extra time is already counted in the limit), USD 200 plus applicable taxes, online proctored or at a test center, no test aides, in English. No prerequisite; related training is highly recommended, with one year of hands-on experience in the tasks of the outline. Valid for 2 years; to recertify you take the current live exam. Passing score: Not published. This outline is the version published on October 9, 2026.

From Databricks's certification page and exam guide, checked Nov 1, 2026.

Domains and weights

  • Domain 1: Developing Code for Data Processing using Python and SQL

    23%

  • Domain 2: Data Ingestion & Acquisition

    12%

  • Domain 3: Data Manipulation

    12%

  • Domain 4: Monitoring and Alerting

    10%

  • Domain 5: Cost & Performance Optimization

    15%

  • Domain 6: Ensuring Data Security and Compliance

    8%

  • Domain 7: Data Governance

    5%

  • Domain 8: Debugging and Deploying

    10%

  • Domain 9: Data Modeling

    5%

On our roadmap this comes after Data Engineer Associate. See every certification.

Practice

240 original practice questions, every option explained with the Databricks documentation page that proves it. Free, no sign-up; progress stays on this device.

Your results on this device →

More practice exams

The lessons, the sample questions on every task page and the first full practice exam are free and stay free. A pack adds the further timed Data Engineer Professional practice exams.

Data Engineer Professional exam pack

$11.99for 12 months

  • Every paid Data Engineer Professional practice exam, timed, with every option explained
  • The next version of this exam included when it changes within your 12 months
  • 12 months of access. One payment, nothing renews by itself.
  • 14-day refund, no conditions
  • 14-day refund, no conditions: ask within 14 days of buying and you get the whole payment back.
  • No pass guarantee. These are practice exams written by us from the exam guide and the Databricks documentation; a score here does not predict your result on the real exam.

Study path

One module per exam domain. Lessons that already exist on BytePatterns are linked; the rest are being written.

  1. Module 1: Developing Code for Data Processing using Python and SQL

    1. 1Bundle project layout: includes, a src package, wheel artifacts and Python resourcesTask 1.1

      Lesson coming

    2. 2Library failures: serverless environments, pipeline dependencies, wheels and requirements filesTask 1.2

      Partly covered by: Images, Layers & Multi-Stage Builds

    3. 3SQL, Python, batch and pandas UDFs, and Unity Catalog functionsTask 1.3

      Lesson coming

    4. 4Streaming pipelines with Auto Loader: file events, schema evolution and modesTask 1.4

      Partly covered by: SQS vs SNS vs EventBridge

    5. 5Jobs from the UI, the Jobs API, the CLI and the SDKTask 1.5

      Lesson coming

    6. 6Streaming table or materialized view: latency, cost and refreshTask 1.6

      Lesson coming

    7. 7AUTO CDC: keys, sequencing, deletes, SCD type 1 and type 2Task 1.7

      Lesson coming

    8. 8Declarative pipelines or hand-written Structured StreamingTask 1.8

      Partly covered by: Message Queues

    9. 9If/else conditions, For each loops and Run ifTask 1.9

      Lesson coming

    10. 10Serverless environments, performance mode, memory and retriesTask 1.10

      Partly covered by: Requests, Limits & HPA, Pods, ReplicaSets & Deployments

    11. 11Testing transformations: transform, assertDataFrameEqual, assertSchemaEqual and pytestTask 1.11

      Lesson coming

    12. 12Stateful streaming: watermarks, output modes, foreachBatch and checkpointsTask 1.12

      Partly covered by: Design Ad Click Aggregation

  2. Module 2: Data Ingestion & Acquisition

    1. 13Kafka, Kinesis, Pub/Sub, files and table formats as sourcesTask 2.1

      Partly covered by: SQS vs SNS vs EventBridge, Moving Data Into AWS

    2. 14Incremental CDC pipelines into Delta and Iceberg-readable targetsTask 2.2

      Partly covered by: Database Replication

    3. 15Lakeflow Connect database connectors: gateway, pipeline and history trackingTask 2.3

      Lesson coming

    4. 16OpenSharing and Clean RoomsTask 2.4

      Lesson coming

    5. 17Lakehouse Federation: connections, foreign catalogs and permissionsTask 2.5

      Lesson coming

  3. Module 3: Data Manipulation

    1. 18Window functions, joins and aggregations at scaleTask 3.1

      Partly covered by: Window Functions, Query Execution Order

    2. 19VARIANT: parse_json, paths, variant_get and shreddingTask 3.2

      Lesson coming

    3. 20AI functions and ai_query in pipelinesTask 3.3

      Partly covered by: Training vs Inference, What Is an LLM

    4. 21Expectations: warn, drop, fail and quarantineTask 3.4

      Partly covered by: Data Readiness for AI

  4. Module 4: Monitoring and Alerting

    1. 22System tables for cost, audit and workload monitoringTask 4.1

      Partly covered by: AWS Cost Levers

    2. 23Monitoring jobs and pipelines with the REST API, CLI and SDKTask 4.2

      Lesson coming

    3. 24The pipeline event logTask 4.3

      Lesson coming

    4. 25Databricks SQL alerts and alert tasksTask 4.4

      Partly covered by: CloudWatch, Alarms & X-Ray

    5. 26Job run states, thresholds and notificationsTask 4.5

      Partly covered by: Observability Basics

  5. Module 5: Cost & Performance Optimization

    1. 27Managed tables, predictive optimization and automatic liquid clusteringTask 5.1

      Lesson coming

    2. 28Deletion vectors, liquid clustering and CLUSTER BY AUTOTask 5.2

      Lesson coming

    3. 29The disk cache and query result cachingTask 5.3

      Partly covered by: Caching, Invalidation and Eviction

    4. 30Change data feed for incremental downstream processingTask 5.4

      Lesson coming

    5. 31Reading the query profileTask 5.5

      Partly covered by: Reading a Query Plan

    6. 32Liquid clustering, partitioning and Z-orderTask 5.6

      Partly covered by: Indexes, Database Sharding

  6. Module 6: Ensuring Data Security and Compliance

    1. 33Least privilege on Unity Catalog objects and workspace resourcesTask 6.1

      Partly covered by: Shared Responsibility & IAM

    2. 34ABAC policies with governed tagsTask 6.2

      Lesson coming

    3. 35Hashing, tokenization, suppression and generalizationTask 6.3

      Partly covered by: Finding and Masking PII, KMS, Envelope Encryption & Private CA

    4. 36PII detection and masking across batch and streamingTask 6.4

      Partly covered by: Finding and Masking PII

    5. 37Purging data for retention and erasure requestsTask 6.5

      Partly covered by: S3: Consistency, Classes, Lifecycle

  7. Module 7: Data Governance

    1. 38Tags and comments for discoveryTask 7.1

      Lesson coming

    2. 39How privileges inherit through catalogs, schemas and objectsTask 7.2

      Partly covered by: Organizations, SCPs & Control Tower

  8. Module 8: Debugging and Deploying

    1. 40Diagnostics: Spark UI, compute logs, system tables and query profilesTask 8.1

      Partly covered by: Tracing a Request

    2. 41Repairing failed runs and overriding parametersTask 8.2

      Lesson coming

    3. 42Deploying bundles: targets, modes, identities and permissionsTask 8.3

      Partly covered by: ConfigMaps, Secrets & Env

    4. 43Git folders in CI/CDTask 8.4

      Lesson coming

  9. Module 9: Data Modeling

    1. 44Table layouts: partition grain, clustering keys and file sizesTask 9.1

      Partly covered by: Database Sharding

    2. 45Dimensional models, materialized views and metric viewsTask 9.2

      Partly covered by: Aggregations & GROUP BY

Every task in the exam guide

The exam guide splits each domain into task statements. Each one has a page with a short summary, the lessons that teach it and open sample questions.

Domain 1: Developing Code for Data Processing using Python and SQL

Domain 2: Data Ingestion & Acquisition

Domain 3: Data Manipulation

Domain 4: Monitoring and Alerting

Domain 5: Cost & Performance Optimization

Domain 6: Ensuring Data Security and Compliance

Domain 7: Data Governance

Domain 8: Debugging and Deploying

Domain 9: Data Modeling

How these questions are made

  • Written by us from the exam guide's task statements and the Databricks documentation — never from real exam content.
  • Every option carries its own explanation and a link to the Databricks page that proves it.
  • A question enters a timed exam only after an independent check; until then it is a practice question.
  • Results are a plain percentage, per domain too — not an imitation of Databricks's scaled score.

Questions about the Data Engineer Professional practice exam

Is the Data Engineer Professional practice exam free?
Yes. The full practice exam (60 questions, 120 minutes) is free with no sign-up, and so are the 240 practice questions, the task pages and the study path. Your attempts are saved in this browser, on this device.
How many questions does it have, and is it timed?
60 questions in 120 minutes: the real Data Engineer Professional pace, scaled to this form. When the time runs out, the exam is submitted as it stands.
Are the answers explained?
After you submit, not during: like the real exam, the timed exam gives no feedback until the end. Then you get your score overall and per exam domain, and every question with each option explained and a link to the Databricks documentation page behind it. In practice mode an answer is explained as soon as you check it.
What does the Data Engineer Professional exam pack add?
3 more timed practice exams (Practice exam 1: 60 questions, 120 minutes; Practice exam 2: 60 questions, 120 minutes; Practice exam 3: 60 questions, 120 minutes), each scored and explained the same way, and the next version of this exam if it changes within your 12 months. 12 months of access. One payment, nothing renews by itself. Everything above stays free. See the pack.
Can I get a refund?
Yes, with no conditions: ask within 14 days of buying and you get the whole payment back. The details are in the terms.
Is this an official Databricks practice exam?
No. BytePatterns is not affiliated with, endorsed or sponsored by Databricks. Every question is written by us from the public exam guide and the Databricks documentation, never from real exam content, and a score here does not predict your result on the real exam. Databricks lists its own preparation resources on its certification page.