How they overlap
Data engineers work in the cloud — they use AWS S3, Redshift, Glue, and Lambda, or Azure Data Factory and Synapse, or Google BigQuery and Dataflow. But the focus is always on data: moving it, transforming it, storing it in ways that support analysis. A cloud architect, by contrast, might design the same company's network security, serverless application architecture, and disaster recovery strategy — none of which involves data pipelines specifically.
Cloud certifications like AWS Solutions Architect Associate are genuinely useful for data engineers because they establish a broader mental model of the cloud environment. But the cloud knowledge a data engineer needs is more specialised — understanding data-specific services in depth — rather than the breadth required of a cloud architect.
Which to focus on
If your goal is working with data specifically — pipelines, warehouses, analytics infrastructure — focus on data engineering and add AWS/Azure data services as part of that learning. If you want broader infrastructure work and are comfortable with the idea that data is just one of many areas you will support, cloud computing or DevOps may be the better primary focus.
For career switchers coming from analytics, SQL, or data adjacent roles, data engineering is usually the more natural path. The skills build more directly from what you already know.