Databricks Data Engineer study guide
Databricks Data Engineer · Work through your exam, one topic at a time.
The Databricks Certified Data Engineer Associate is a proctored, entry-level certification that assesses a person's ability to use the Databricks Data + AI Platform to execute foundational data engineering tasks. It is aimed at practitioners with hands-on experience building ETL pipelines - data engineers, analytics engineers, and developers moving onto the lakehouse - and serves as a structured way to demonstrate baseline platform skills. The Databricks Data Engineer study guide has 7 sections and about 2,156 words.
01Databricks Intelligence Platform
Every Databricks deployment splits into a control plane (Databricks-managed: notebook storage, job scheduler, cluster manager, Unity Catalog metadata, web UI) and a data plane (your cloud account for classic compute, or Databricks-managed for serverless). Data stays in your cloud storage; only metadata and control traffic cross into the control plane.
286 words, about 1 min02Data Ingestion and Loading
Auto Loader ( spark.readStream.format('cloudFiles') ) incrementally discovers new files using directory listing (cheap at small scale) or file notification via SNS/SQS or Event Grid (efficient at large scale). It infers and stores schema in a checkpoint, and evolves it via cloudFiles.schemaEvolutionMode ( addNewColumns default, rescue , failOnNewColumns , none ) plus schemaHints to pin types.
299 words, about 1 min03Data Transformation and Modeling
Bronze preserves raw data, silver holds conformed and deduplicated entities, gold holds business aggregates. Delta Lake provides ACID transactions, schema enforcement (with mergeSchema opt-in), time travel, MERGE , deletion vectors, and liquid clustering.
314 words, about 2 min04Working with Lakeflow Jobs
A Lakeflow Job is a DAG of tasks. Task types include notebook, Python script or wheel, SQL query or file, pipeline (Lakeflow / Delta Live Tables), dbt, For each (loop over an array) and If/else (conditional branch).
303 words, about 2 min05Implementing CI/CD
Databricks Asset Bundles (DABs) describe jobs, pipelines, notebooks, and clusters as code in databricks.yml . The file contains a bundle name, variables , resources (jobs, pipelines, and so on), and one or more targets (dev, staging, prod), each specifying a workspace host and overrides.
307 words, about 2 min06Troubleshooting, Monitoring, and Optimization
Spark UI / query profile : stages → tasks. Look for shuffle read/write volume, spill (memory versus disk), and task duration skew (max versus median).
313 words, about 2 min07Governance and Security
The namespace has three levels: catalog.schema.table , plus volumes and functions. One metastore per region attaches to workspaces.
334 words, about 2 min