Which is harder, DP-700 or the Google Professional Data Engineer?

The Google exam is positioned as a professional, expert-level credential and Google recommends three or more years of experience, including a year on Google Cloud. DP-700 is an associate-level exam. Both are hands-on and judgement-based rather than memorisation tests, but on stated level and recommended experience the Google PDE is the more demanding of the two.

You can, and some engineers who work across clouds do. But for most people the better use of time is to certify on the cloud you actually work with. Multi-cloud certs make most sense once you genuinely operate pipelines on more than one platform, not as a way to hedge before you have a job.

Why does DP-700 expire after one year when the Google cert lasts two?

Different renewal models. Microsoft requires annual renewal for its role-based certifications, but renewal is a free, online, open-book assessment on Microsoft Learn. The Google certification is valid for two years and then requires a paid recertification exam (around US$100; confirm before booking). So DP-700 renews more often but at no cost, while the Google cert renews less often but for a fee.

Which pays more or is more in demand?

Demand follows the cloud, not the badge. In organisations standardised on Google Cloud, the PDE is the credential employers look for; in Microsoft-centric and many DACH enterprises adopting Fabric, DP-700 maps to the work. Look at the actual job postings you are targeting and certify on whichever cloud they name.

I am new to data engineering. Where should I start?

Neither of these is an ideal first exam. The Google PDE assumes years of real pipeline experience. DP-700 has no formal prerequisite but expects you to be comfortable with SQL, PySpark and KQL across the full Fabric workflow. If you are starting from scratch, build core data skills first, and on the Google side many people take the Associate Cloud Engineer before the PDE.

Do these certs replace older ones?

DP-700 is the Fabric-era successor to the retired DP-203 (Azure Data Engineer Associate, retired 31 March 2025); where DP-203 was built around Azure Synapse and Azure Data Factory, DP-700 is built around Microsoft Fabric and OneLake. The Google Professional Data Engineer is an established credential that Google updates periodically rather than replaces.

Head-to-head comparison

DP-700 vs Google Professional Data Engineer: which cloud data cert?

By The Exam Atlas Editorial Team · Verified 2026-06-06

Our verdict

This is rarely a free choice. Pick the certification that matches the cloud your employer actually runs. Choose DP-700 if your data stack is Microsoft Fabric, OneLake and Power BI. Choose the Google Professional Data Engineer if your stack is BigQuery, Dataflow and Pub/Sub. The platform on the job postings you are targeting decides this, not prestige.

Side by side

The numbers that decide it, lined up across every dimension that matters.

	DP-700	PDE
Cloud ecosystem	Microsoft Fabric, OneLake, Power BI	Google Cloud (BigQuery, Dataflow, Pub/Sub)
Level	Associate	Professional (expert-level)
Exam length	100 minutes	120 minutes
Questions	Not published by Microsoft	40-50 questions
Passing score	700 / 1000 (scaled)	Not published (pass/fail)
Exam fee	~US$165 (priced by region)	US$200 (+ tax)
Validity	1 year (free online renewal)	2 years (US$100 recert)
Recommended experience	SQL, PySpark, KQL; no formal prerequisite	3+ years industry, 1+ year on GCP

Full exam pages: Microsoft Fabric Data Engineer (DP-700) · Google Cloud Professional Data Engineer

The Microsoft Fabric Data Engineer (DP-700) and the Google Cloud Professional Data Engineer both certify that you can build and run data pipelines in the cloud. The catch is that they certify it on two different clouds. Here is the detailed comparison, beyond the table above.

The core difference

Both credentials cover the same craft: ingesting data, choosing the right storage, building batch and streaming pipelines, and keeping them secure, monitored and optimised. What differs is the platform you do it on.

DP-700 is built around Microsoft Fabric and OneLake. You work with Lakehouse and Warehouse, Spark notebooks, Dataflows Gen2, pipelines, and real-time data with KQL and Eventhouse, and you transform data with SQL, PySpark and KQL.

The Google Professional Data Engineer is built around Google Cloud. You are expected to know when to reach for BigQuery versus Bigtable, Dataflow versus Dataproc, and Pub/Sub for streaming, and to reason about cost, latency and scale.

So the real question is not “which is better” but “which cloud does the work I want to do run on?” Answer that and the choice is mostly made.

Cost compared

The headline fees are close, but the renewal models differ:

DP-700: around US$165, though Microsoft prices the exam by region, so confirm the current figure on the official page. Study materials on Microsoft Learn are free, and a Fabric trial capacity is available. Renewal is a free online assessment each year.
Google PDE: US$200 plus tax. The Google Cloud free tier, a BigQuery sandbox and official sample questions are free for practice. Recertification before the two-year expiry is a separate paid exam (around US$100; confirm before booking).

Over time, DP-700 is the cheaper credential to keep current because renewal costs nothing, even though you renew more often.

Difficulty and time

Both are hands-on and judgement-based, but they sit at different levels:

DP-700 is an associate-level exam: 100 minutes, with a number of questions Microsoft does not publish and possible interactive question types. The pass mark is a scaled 700 out of 1000, not a simple percentage. There is no formal prerequisite, but you need to be comfortable with SQL, PySpark and KQL.
Google PDE is a professional, expert-level exam: 120 minutes, 40 to 50 multiple-choice and multiple-select questions. Google does not publish a fixed passing score; the result is pass or fail. Google recommends 3+ years of industry experience, including 1+ year on Google Cloud, and it shows in the scenario questions.

Neither is a memorisation exam. On stated level and recommended experience, the Google PDE is the heavier lift; DP-700 is more accessible but still expects real Fabric skills.

Platform and ecosystem

This is usually the deciding factor:

DP-700 lives in the Microsoft data ecosystem. It pairs naturally with PL-300 (Power BI Data Analyst) for the reporting side, and is increasingly requested in Microsoft-centric organisations and across many DACH enterprises adopting Fabric.
Google PDE lives in the Google Cloud ecosystem and is the flagship data-engineering credential there, consistently sought by employers running BigQuery and Dataflow.

If your employer (or target employer) has standardised on one cloud, that decides it. A Fabric certification carries little weight at a BigQuery shop, and the reverse is just as true.

Career outcomes

DP-700 maps to: data engineer, analytics engineer, ETL/ELT developer and Fabric data engineer roles inside the Microsoft stack.
Google PDE maps to: data engineer, analytics engineer and platform/ETL roles building and operating pipelines at scale on Google Cloud.

The job titles overlap almost entirely. The difference is the tools listed in the job description: Fabric, OneLake and Power BI on one side; BigQuery, Dataflow, Pub/Sub and Dataproc on the other.

How to decide

Ignore prestige and answer one question: which cloud does your team run, or which cloud do the jobs you want run on?

Microsoft Fabric, OneLake, Power BI → DP-700.
Google Cloud, BigQuery, Dataflow, Pub/Sub → Google Professional Data Engineer.
Genuinely undecided and early in your career → build core data skills first; DP-700 is the more accessible entry point, while the Google PDE is better earned after real GCP pipeline experience.

Both are cloud-specific by design. Certify on the platform that pays your bills, not the one with the better-known logo.

Which should you choose?

Choose DP-700 if

Data engineers in Microsoft-centric organisations adopting Microsoft Fabric, OneLake and Power BI, who want the current associate-level Fabric data-engineering credential.

Choose PDE if

Data engineers with real Google Cloud experience who build pipelines on BigQuery, Dataflow, Pub/Sub and Dataproc and want the flagship GCP data-engineering credential.

Our specialty · side by side

Related comparisons

Other like-for-like match-ups featuring DP-700 or PDE.

VS DP-700 vs Databricks Data Engineer Associate: which should you choose? Compare →

Where these exams lead

Career paths featuring these exams

See where DP-700 and PDE sit in a longer certification sequence.

How to become a data analyst: the certs, then the path to data engineer View path →

FAQ

Which is harder, DP-700 or the Google Professional Data Engineer?: The Google exam is positioned as a professional, expert-level credential and Google recommends three or more years of experience, including a year on Google Cloud. DP-700 is an associate-level exam. Both are hands-on and judgement-based rather than memorisation tests, but on stated level and recommended experience the Google PDE is the more demanding of the two.
Can I take both?: You can, and some engineers who work across clouds do. But for most people the better use of time is to certify on the cloud you actually work with. Multi-cloud certs make most sense once you genuinely operate pipelines on more than one platform, not as a way to hedge before you have a job.
Why does DP-700 expire after one year when the Google cert lasts two?: Different renewal models. Microsoft requires annual renewal for its role-based certifications, but renewal is a free, online, open-book assessment on Microsoft Learn. The Google certification is valid for two years and then requires a paid recertification exam (around US$100; confirm before booking). So DP-700 renews more often but at no cost, while the Google cert renews less often but for a fee.
Which pays more or is more in demand?: Demand follows the cloud, not the badge. In organisations standardised on Google Cloud, the PDE is the credential employers look for; in Microsoft-centric and many DACH enterprises adopting Fabric, DP-700 maps to the work. Look at the actual job postings you are targeting and certify on whichever cloud they name.
I am new to data engineering. Where should I start?: Neither of these is an ideal first exam. The Google PDE assumes years of real pipeline experience. DP-700 has no formal prerequisite but expects you to be comfortable with SQL, PySpark and KQL across the full Fabric workflow. If you are starting from scratch, build core data skills first, and on the Google side many people take the Associate Cloud Engineer before the PDE.
Do these certs replace older ones?: DP-700 is the Fabric-era successor to the retired DP-203 (Azure Data Engineer Associate, retired 31 March 2025); where DP-203 was built around Azure Synapse and Azure Data Factory, DP-700 is built around Microsoft Fabric and OneLake. The Google Professional Data Engineer is an established credential that Google updates periodically rather than replaces.