Google Cloud
Data & AI · Professional
The GCP Data Engineer syllabus published by Google Cloud covers Data ingestion and processing, Data warehousing and analytics systems, Data governance and security and Reliability, monitoring and cost. This is the certification's own scope — it is not a claim about which parts Koshish has banked, and the bank status is stated separately below.
Every area Google Cloud examines for Google Cloud Professional Data Engineer.
Data ingestion and processing
Data warehousing and analytics systems
Data governance and security
Reliability, monitoring and cost
The same practice loop the rest of the platform runs, scoped to this certification's domains once its bank exists.
Subject- and topic-filtered practice across the Data & AI domains the certification covers
A daily plan that blends new practice with FSRS spaced revision of what you have already attempted
Per-topic ability estimates (IRT theta and BKT mastery) that surface your weakest domains first
A rationale on every attempt, reactive to the specific mistake you made rather than a generic explanation
Weak-topic analysis that decides what comes next instead of leaving the order to you
Said plainly rather than implied by the syllabus list above.
No verified GCP Data Engineer question bank exists yet, so no practice sessions or mock exams are published for this certification. The syllabus and exam information above are published now; the bank appears here once it is verified.
Google Cloud sets the exam content, timing and policy. Those details are restated from the issuer's published material and can change between versions — treat the issuer's own page as the authority for your attempt.
Case-study and scenario essay practice, lab environments and hands-on performance exams are outside written-MCQ practice and are not claimed here.
Questions
Not yet. The GCP Data Engineer question bank does not exist today, so we are not advertising practice sessions that would open onto an empty screen. The data & ai syllabus, exam pattern and eligibility are published here now, and the bank will be listed as soon as its questions pass verification.
Google Cloud Professional Data Engineer is examined across these areas: Data ingestion and processing, Data warehousing and analytics systems, Data governance and security and Reliability, monitoring and cost. A proctored exam with scenario-based multiple-choice and multi-select items covering the professional data engineer blueprint, including designing data processing and data warehouse systems.
Google Cloud publishes no formal prerequisites for this exam; it recommends relevant experience before attempting it. Google Cloud is the authority for the criteria that apply to your attempt.
Credentials renew every two years through a renewal assessment, per Google Cloud's certification policy.