This guide targets Databricks Certified Data Engineer Associate (DE-ASSOC), Databricks’ associate-level certification for notebook-based ETL, Delta tables, Lakeflow pipelines, production jobs, and Unity Catalog governance. As of April 15, 2026, Databricks’ live certification page and the current January 2026 exam guide both use the same 5-section public blueprint. This guide follows that live structure directly.
Databricks Data Intelligence Platform: Databricks workspace, compute, storage abstractions, governance, and managed data-engineering features working together as one operating environment.
Unity Catalog: Databricks governance layer for catalogs, schemas, tables, permissions, lineage, and sharing.
At a glance
DE-ASSOC does not reward raw Spark syntax recall by itself. Strong answers usually start by classifying the question into the right lane first: platform fit, development and ingestion, transformation logic, production operations, or governance. The trap is often not a silly answer. The trap is choosing a fix from the wrong layer of the Databricks workflow.
Exam fact
Current official value
Scored questions
45 multiple-choice
Time limit
90 minutes
Registration fee
USD 200
Delivery
Online or test center
Recommended experience
Roughly 6 months of hands-on Databricks work
Validity
2 years
Guide model
5 blueprint chapters -> 15 section lessons
The current exam guide PDF was published in January 2026 for the version live as of November 30, 2025. Databricks publishes the section objectives directly, so this guide stays rooted to the same five-part map rather than inventing a generic data-engineering curriculum.
Official chapter map
1. Platform: platform value, workspace behavior, performance-aware defaults, and compute fit
2. Ingestion: notebooks, Databricks Connect, Auto Loader, and debugging
3. Processing: medallion design, Lakeflow pipelines, DDL and DML, PySpark DataFrames, and transformation performance
4. Pipelines: Asset Bundles, workflows, repair and rerun, serverless jobs, and Spark UI triage
5. Governance: managed versus external tables, Unity Catalog permissions, auditability, lineage, Delta Sharing, and federation
Use this exam guide in order
Start with the study plan if you want a practical 30 / 60 / 90 day route.
Work through the five official chapters in order, starting with Platform and Ingestion.
Use the cheat sheet after you understand the chapter logic well enough to separate near-miss answers.
Work through the sample questions to practice ingestion, transformation, operations, and governance prompts with full explanations.
Keep the glossary open when Lakeflow, Unity Catalog, Delta, and workflow terms start to blur together.
Use the FAQ when you want exam-fit, readiness, or last-week guidance.
Keep the resources page nearby while you work through the official Databricks guide and primary docs.
flowchart LR
A["1. Platform and compute fit"] --> B["2. Development and ingestion workflow"]
B --> C["3. Processing and transformation logic"]
C --> D["4. Deployment, jobs, and runtime triage"]
D --> E["5. Governance, sharing, and federation"]
E --> F["Cheat sheet, glossary, and final review"]
What strong answers usually do
classify whether the stem is mainly about platform choice, data ingestion, pipeline logic, deployment behavior, or governance
distinguish interactive development workflow from scheduled production workflow
prefer managed, observable, repeatable pipeline behavior over manual notebook habits
treat Unity Catalog, lineage, auditability, and sharing as part of the platform design rather than post-processing chores