Databricks Certified Data Engineer Professional

The Databricks Certified Data Engineer Professional certification exam by Databricks lasts approximately 120 minutes, with a passing score of 70%.

The Databricks Certified Data Engineer Professional practice question bank includes 177 questions across 3 levels (approximately 59 per level), each of which is available in three wording variants. That gives you up to 531 practice question variations to study. On every attempt, questions appear in random order and answer options are shuffled, so each session evaluates your knowledge from a fresh angle.

Databricks Certified Data Engineer Professional is a PROFESSIONAL level certification offered by Databricks. Preparation is considered very complex and typically requires expert level experience.

Databricks Certified Data Engineer Professional is organized into 10 exam domains, starting with Developing Code for Data Processing using Python and , Data Ingestion & Acquisition, Data Transformation, Cleansing, and Quality. Practice with the Certilum diagnostic engine to simulate the Databricks exam, pinpoint weak domains and measure your readiness before test day.

The Databricks Certified Data Engineer Professional exam has a difficulty score of 7.8/10 (Expert Level). Preparation complexity is very complex. It typically requires expert level experience. With a passing score of 70%, thorough preparation is recommended. Certilum's diagnostic engine helps you identify weak domains before test day.

• Designing and implementing multi‑hop data pipelines
• Optimizing performance of Spark jobs and Delta tables
• Configuring data sharing and federation via Delta Sharing and Unity Catalog
• Applying data security measures (row/column-level masking, ACLs)
• Implementing monitoring and alerting for production pipelines
• Debugging and deploying pipelines using CI/CD and Repos

• 1+ year of active Databricks usage
• Solid knowledge of Python and
• Familiarity with Apache Spark concepts

High – requires deep understanding of Spark internals, Delta Lake, streaming, security models, and production deployment concepts.

This certification represents an advanced benchmark for data engineers architecting enterprise-scale solutions on the Lakehouse platform. Certilum recommends it for seasoned professionals seeking to validate expertise in complex pipeline orchestration, performance tuning at scale, and advanced Unity Catalog governance across multi-workspace environments. The exam's rigorous focus on architectural decision-making, optimization strategies, and production-ready reliability makes it essential for lead engineers and architects driving transformational data initiatives in large enterprises.

Focus on hands-on labs: create end‑to‑end pipelines in Databricks workspaces. Master Delta Lake features (OPTIMIZE, Z‑order, Liquid Clustering) and Structured Streaming. Review Unity Catalog administration and performance tuning techniques. Use official Databricks Academy courses and practice exams.