If you already hold a Databricks Data Engineer certification, you are not starting the AWS DEA-C01 from zero. The engineering concepts transfer; what is new is the AWS service catalog and how the exam maps familiar problems onto specific services. This plan skips what you know and targets what you do not.
Last updated July 2026.
The mental models you built for the lakehouse map cleanly onto the AWS exam. You already reason about these; you just relabel them:
The shift in mindset: Databricks gives you one integrated platform. AWS gives you a menu of services, and the exam is largely about choosing the right one for a scenario. Your job is to learn the menu, not relearn data engineering.
Budget most of your study time here. These have no clean Databricks equivalent:
DEA-C01 is 65 questions in 130 minutes and costs $150 USD. The scored content splits across four domains:
| Domain | Weight | Your Databricks head start |
|---|---|---|
| 1. Data Ingestion and Transformation | 34% | High: ingestion and ETL concepts transfer well |
| 2. Data Store Management | 26% | Medium: table-format ideas help, service choices are new |
| 3. Data Operations and Support | 22% | Medium: orchestration transfers, tooling is new |
| 4. Data Security and Governance | 18% | Low: IAM and Lake Formation are mostly new ground |
Domain weights from the official AWS Certified Data Engineer Associate (DEA-C01) exam guide.
Domain 1 is the largest slice and the one your background most directly helps with, so it is efficient to confirm those transfers quickly and then pour time into Domain 4, where you have the least head start.
The engineering concepts in Domain 1 transfer well, which is a real head start on the largest domain. The AWS service catalog and Domain 4 security topics are new, so you still need dedicated study, just less on the fundamentals.
65 questions in 130 minutes for $150 USD, across four domains weighted 34%, 26%, 22%, and 18%. Confirm current details in the official AWS exam guide before you book.
Domain 4, Data Security and Governance. AWS IAM policy types and Lake Formation permissions have no clean Unity Catalog equivalent and are where candidates with a Databricks background tend to lose the most points.
No. Your streaming vs batch trade-off knowledge transfers. What is new is the mapping onto Kinesis Data Streams, Amazon Data Firehose, and Amazon Managed Service for Apache Flink, and knowing which one fits a given scenario.
The AWS Data Engineer Associate course is built around exactly these service-choice decisions, so you can spend your time on what is new instead of what you already know.
Open the AWS DEA course →