Databricks Certified-Data-Engineer-Professional : Databricks Certified Data Engineer Professional

Exam Code: Certified-Data-Engineer-Professional
Exam Name: Databricks Certified Data Engineer Professional
Updated: Oct 10, 2026 Q&As: 250 Questions and Answers

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About Databricks Certified-Data-Engineer-Professional Exam

Certification exams change, and so do we. Your Certified-Data-Engineer-Professional purchase from DumpsTests includes 365 days of free updates, so your Databricks Certified Data Engineer Professional practice questions always reflect the current 2026 syllabus.

Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:

Section	Objectives
Data Ingestion & Acquisition	- Design and implement data ingestion pipelines 1. Build append-only pipelines for batch and streaming data using Delta 2. Ingest data from message buses and cloud storage 3. Ingest Delta Lake, Parquet, ORC, Avro, JSON, CSV, XML, Text, and Binary data
Cost & Performance Optimisation	- Query Performance 1. Identify inefficient joins and excessive data shuffling 2. Use Query Profile to identify performance bottlenecks - Cost Optimization 1. Understand how Unity Catalog managed tables reduce operational overhead - Delta Optimization 1. Understand deletion vectors and liquid clustering 2. Use Change Data Feed to address streaming table limitations and improve latency 3. Apply data skipping and file pruning techniques
Data Modelling	- Scalable Data Models 1. Understand Liquid Clustering versus partitioning and Z-Ordering 2. Design and implement scalable data models using Delta Lake 3. Optimize data layout using Liquid Clustering - Dimensional Modelling 1. Design dimensional models for analytical workloads
Debugging and Deploying	- Deploying CI/CD 1. Build and deploy Databricks resources using Databricks Asset Bundles 2. Integrate Git-based CI/CD workflows using Databricks Git Folders - Debugging and Troubleshooting 1. Use Lakeflow Spark Declarative Pipelines event logs and Spark UI for debugging 2. Use Spark UI, cluster logs, system tables, and query profiles for diagnostics 3. Analyze errors and remediate failed job runs
Developing Code for Data Processing using Python and SQL	- Building and Testing ETL Pipelines 1. Build production-ready batch and streaming pipelines using Lakeflow Spark Declarative Pipelines and Auto Loader 2. Configure environments, dependencies, memory, and retry behavior 3. Compare Spark Structured Streaming and Lakeflow Spark Declarative Pipelines 4. Create and automate ETL workloads using Jobs through UI, APIs, and CLI 5. Compare streaming tables and materialized views 6. Develop unit and integration tests for data processing code 7. Use control flow operators in pipeline components 8. Use APPLY CHANGES APIs for change data capture - Using Python and Tools for Development 1. Design and implement scalable Python project structures optimized for Databricks Asset Bundles 2. Develop User-Defined Functions using Pandas/Python UDFs 3. Manage and troubleshoot third-party library installations and dependencies
Monitoring and Alerting	- Alerting 1. Configure Lakeflow Jobs notifications for job status and performance issues 2. Use SQL Alerts for data quality monitoring - Monitoring 1. Use Query Profiler and Spark UI to monitor workloads 2. Use system tables for resource, cost, audit, and workload monitoring 3. Use Lakeflow Spark Declarative Pipelines event logs for monitoring 4. Use Databricks REST APIs and CLI for monitoring jobs and pipelines
Data Sharing and Federation	- Lakehouse Federation 1. Configure Lakehouse Federation with appropriate governance - Delta Sharing 1. Share live Lakehouse data with external computing platforms 2. Configure sharing with external platforms using the open sharing protocol 3. Configure Databricks-to-Databricks Sharing
Data Governance	- Unity Catalog Permissions 1. Understand the Unity Catalog permission inheritance model - Metadata and Discoverability 1. Create and maintain descriptions and metadata for enterprise data
Data Transformation, Cleansing, and Quality	- Data Quality 1. Develop data quarantining processes for invalid data 2. Apply data quality controls using Lakeflow Spark Declarative Pipelines or Auto Loader - Advanced Data Transformation 1. Apply window functions, joins, and aggregations to large datasets 2. Write efficient Spark SQL and PySpark transformations
Ensuring Data Security and Compliance	- Data Security 1. Use ACLs to secure workspace objects and enforce least privilege 2. Apply anonymization and pseudonymization techniques 3. Use row filters and column masks for sensitive data - Compliance 1. Develop data purging solutions according to data retention policies 2. Implement pipelines that detect and mask personally identifiable information

Databricks Certified-Data-Engineer-Professional FAQs: What Every Candidate Asks

What is the Databricks Certified Data Engineer Professional exam?

The Certified-Data-Engineer-Professional exam, officially titled Databricks Certified Data Engineer Professional, is the qualifying test for the Databricks Certification certification from Databricks, a credential at the Professional level. Passing it proves you have the skills employers look for in certified professionals, and it can also support progress toward related credentials such as Databricks Certified Data Engineer Associate.

How many questions are on the Certified-Data-Engineer-Professional exam, and how long does it take?

The Databricks Certified Data Engineer Professional exam gives you 120 minutes to work through 59 scored questions questions. That is a steady pace with little room for second-guessing, so train yourself to read each question once, flag the difficult ones, and keep moving. Before exam day, sit at least two full timed sessions in the DumpsTests test engine — when the clock feels familiar, it stops being a threat.

What is the passing score for Certified-Data-Engineer-Professional, and how much does the exam cost?

You need Not publicly specified in the current official exam guide to pass, and the official registration fee is USD 200, plus applicable taxes as required by local law. Fall short and you pay that fee in full again for every retake, which makes solid preparation the cheaper option by far. Work through the DumpsTests practice questions until you score comfortably above the passing mark, then book your seat.

Are there any prerequisites for the Certified-Data-Engineer-Professional exam?

No mandatory prerequisite. Databricks recommends related course attendance and approximately one year of hands-on experience performing the Data Engineering tasks covered by the exam. Eligibility rules can change over time, so before you register, confirm the latest requirements on the official exam page: Databricks Certified-Data-Engineer-Professional exam overview.

Can I try the Certified-Data-Engineer-Professional practice questions before I buy?

Yes. DumpsTests offers a free PDF demo for the Databricks Certified Data Engineer Professional exam so you can judge the quality of our questions and answers before paying anything. Every purchase also comes with 365 days of free updates, and once that period expires you can extend your update service at a 50% discount.

What happens if I don't pass, and how is my order delivered?

Your purchase is protected by a 100% money-back guarantee. If you sit the corresponding Certified-Data-Engineer-Professional exam within 60 days of buying and do not pass, send us a scan of your exam enrollment slip together with your official Score Report (PDF) within 2 days of the exam date — the candidate name must match the payer's name — and we will process your full refund within 7 days. Please note that exams taken within 3 days of purchase, materials downloaded without ever sitting the exam, free products, and expired orders are not covered. If you would rather not have a refund, you can exchange your order for two exam products of equal value, free of charge, and keep the update service on your original purchase.

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What topics are covered in the Certified-Data-Engineer-Professional exam?

The Databricks Certified Data Engineer Professional syllabus is organized into 10 domains. The main areas include Data Modelling, Monitoring and Alerting, and Cost & Performance Optimisation. Scroll up to the Exam Topics section above for the complete, current outline before you plan your study schedule.

Databricks Certified Data Engineer Professional Sample Questions:

Question #1

Which statement describes the correct use of pyspark.sql.functions.broadcast?

A. It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.
B. It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.
C. It marks a column as small enough to store in memory on all executors, allowing a broadcast join.
D. It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.
E. It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.

Reveal Solution Discussion 0

Correct Answer: A 🗳️