I'm a Data Platform Engineer based in Milan, and I hold both the Databricks Certified Data Engineer Associate and the Databricks Certified Data Engineer Professional certifications. I've sat the same exams you're preparing for. I use Databricks day by day so it's not just a course for its own purpose.

I work in the Data Management team at Prada Group, leading end-to-end delivery of ML applications, data science tools and business reporting. Before that, five years at Data Reply IT building AWS and Databricks platforms for financial services: ingestion pipelines, Delta Lakes, dbt models, data governance on DataHub, and real-time observability. Ten-plus years in data, three clouds in production, and an MSc in Computer Engineering from the University of Pisa.

That production experience is what shapes my practice questions. The exam is full of scenarios that look academic until you've actually hit them: the MERGE that quietly duplicated rows, the VACUUM retention window that mattered more than anyone expected, the streaming job that ran fine for three weeks and then didn't. I write questions around the things that bite you in real pipelines, because those are the ones the exam is testing too.

I also believe a question you get right by luck teaches you nothing. So every question in my courses comes with a full explanation: why the correct answer is correct, why each of the other options is wrong, and where to read more in the official documentation.

Outside work I write about Databricks and data engineering, I'm building an open-source project on operational ontologies, and I run — which is where most of the explanations get drafted in my head.