Google Cloud Professional Data Engineer vs AWS Machine Learning Specialty (MLS-C01)
| Factor | ✅ Google Cloud Professional Data Engineer | AWS Machine Learning Specialty (MLS-C01) |
|---|---|---|
| Vendor | Google Cloud | Amazon Web Services |
| Level | Advanced | Advanced |
| Exam Cost | $200 | $300 |
| Pass Rate | 55% | 55% |
| Avg Salary | $145K–$175K | $145K–$180K |
| Difficulty |
Hard
★★★★☆
|
Hard
★★★★☆
|
| Best For | Data engineers and ML engineers with solid GCP experience building production pipelines. | Data scientists and ML engineers with 1+ year of ML experience on AWS.… |
| Expiry | Typically 3 years — renewal at cloud.google.com | Check aws.amazon.com |
| Full Guide | View guide → | View guide → |
Which Should You Choose?
The right certification depends on your current role, target employer, geography, and the specific skills gap you're trying to close. Here's a practical breakdown:
✅ Choose Google Cloud Professional Data Engineer if…
You're targeting roles at organisations that specifically require Google Cloud credentials, or you're already working within the Google Cloud ecosystem. The Google Cloud Professional Data Engineer carries the strongest recognition among Google Cloud customers and partners, and its salary premium of $145K–$175K is well-documented in the job market.
Full Guide →Consider AWS Machine Learning Specialty (MLS-C01) if…
You're targeting organisations in the Amazon Web Services ecosystem, or the AWS Machine Learning Specialty (MLS-C01) is more commonly required in your target industry or geography. Salary data: $145K–$180K. Specialty certification for machine learning engineers on AWS. Validates ability to design, implemen…
Full Guide →Detailed Analysis — Google Cloud Professional Data Engineer
Strengths
- ✓Issued by Google Cloud — one of the most trusted credential authorities in Data & AI
- ✓Salary premium of $145K–$175K documented across multiple independent sources
- ✓Exam fee of $200 — strong ROI relative to salary gain
- ✓Global recognition at enterprise employers, government agencies, and consulting firms
- ✓Covers 5 core domains including: BigQuery & data warehousing, Dataflow & Pub/Sub pipelines, Cloud ML & AI services
Considerations
- ◆Pass rate is approximately 55% — structured preparation is essential, not optional
- ◆Requires significant hands-on experience — not suitable for complete beginners
- ◆Renewal required — check current requirements at cloud.google.com
Made your decision? Start your preparation today.
Google Cloud Professional Data Engineer Full Guide → Study Roadmap → Salary Data →