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Google Cloud Professional Data Engineer

Issued by Google Cloud. Below is what it costs, how long it lasts, and what it actually signals — with the date we checked.


Google Cloud Professional Data Engineer

Free to learn · paid certificate Recognized

The honest cost
Cost$200
Validity2 years — note this is SHORTER than Google's ML Engineer certificate, which runs 3 years.
RenewalRenew within the eligibility period before expiry via Google's renewal process.
AssessmentProctored exam — two hours, 40–50 multiple choice and multiple select questions, online- or onsite-proctored
ProctoredYes
Verify viaunknown
Cost per active year$100/yr200 ÷ 2

Google's role-mapped data engineering credential. Recommended experience is 3+ years in industry including 1+ year on Google Cloud.

Read this before you buy

Watch the validity difference: this certificate lasts 2 years where Google's ML Engineer lasts 3, so it costs $100 per active year against the ML Engineer's $67. Same sticker price, meaningfully different running cost.

· Official page

How we know

Fee, validity, duration, format and prerequisites read verbatim from Google's official exam page 2026-07-26: "Registration fee : $200 (plus tax where applicable)", "Validity period : 2 years", "Prerequisites : None".

· https://cloud.google.com/learn/certification/data-engineer

Free preparation

Free resources first. Everything below is free to use; the exam itself is the paid part.

Microsoft Learn — Data Engineer career path

Free to learn · no certificate

Free structured career path from Microsoft covering ingestion, storage and transformation.

Apache Airflow official tutorial

Free to learn · no certificate

Orchestration is a core daily skill and Airflow's own tutorial is free. We have not measured how often Airflow specifically is named in job ads.

dbt documentation — introduction

Free to learn · no certificate

Transformation-as-code. The documentation is free to read; dbt Core is open source, though we have not verified the boundary between free and paid tiers on their pricing page.

Used by these roles

  • Data Engineer (AI/ML) — You build and run the pipelines that get data to the models, reliably and on time.