Databricks Data Engineer Associate cheat sheet

Exam at a glance

Domain weightings

How much of the exam each domain covers. Spend your study time in proportion — the heavier the domain, the more questions you'll see.

Key terms

Lakehouse

A lakehouse is an architecture that combines the low-cost storage of a data lake with the management and performance features of a data warehouse. The Data Engineer exam covers the Databricks lakehouse as its platform foundation.

Delta Lake

Delta Lake is an open storage layer that brings ACID transactions, time travel, and schema enforcement to data lakes. The Data Engineer exam covers Delta tables and operations such as OPTIMIZE and VACUUM.

Medallion architecture

The medallion architecture is a data design pattern that refines data through bronze, silver, and gold layers. The Data Engineer exam covers it for modeling data across the lakehouse.

Auto Loader

Auto Loader is a Databricks feature that incrementally and efficiently ingests new files from cloud storage as they arrive. The Data Engineer exam covers it, with COPY INTO, in the data ingestion domain.

Structured Streaming

Structured Streaming is the Spark engine for scalable, fault-tolerant stream processing using the same DataFrame API as batch. The Data Engineer exam covers streaming ingestion basics with it.

MERGE

MERGE is a SQL operation that performs upserts — inserting, updating, or deleting rows in a Delta table based on a match condition. The Data Engineer exam covers MERGE for change data in transformations.

Spark SQL

Spark SQL is the Spark module for querying structured data with SQL and the DataFrame API. The Data Engineer exam covers Spark SQL and PySpark for data transformation and modeling.

PySpark

PySpark is the Python API for Apache Spark, used to build data transformations programmatically. The Data Engineer exam covers PySpark alongside Spark SQL for transformation and modeling.

Lakeflow Jobs

Lakeflow Jobs (formerly Databricks Workflows) is the orchestration service for scheduling and running multi-task data pipelines. The Data Engineer exam covers task dependencies, scheduling, and retries with it.

Lakeflow Declarative Pipelines

Lakeflow Declarative Pipelines (formerly Delta Live Tables) is a framework for building reliable declarative data pipelines with built-in quality expectations. The Data Engineer exam covers it within Lakeflow Jobs.

Databricks Asset Bundles

Databricks Asset Bundles are a way to package code, jobs, and configuration as version-controlled projects for deployment across environments. The Data Engineer exam covers them for CI/CD.

Z-ordering

Z-ordering is a Delta Lake optimization that co-locates related data in the same files to speed up queries that filter on those columns. The Data Engineer exam covers it for performance optimization.

Unity Catalog

Unity Catalog is the Databricks governance layer providing a three-level namespace, access control, and data lineage across the lakehouse. The Data Engineer exam covers it in the governance and security domain.

Spark UI

The Spark UI is the web interface that shows jobs, stages, and tasks for diagnosing and tuning Spark workloads. The Data Engineer exam covers interpreting it for troubleshooting and optimization.