SnowPro Advanced: Data Engineer (DEA-C02) Exam Blueprint

DEA-C02

750Passing Score
$375Price
2Languages
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What This Exam Validates

The SnowPro Advanced: Data Engineer exam, certified by Snowflake, covers sourcing data from data lakes, transforming and replicating across cloud platforms, designing near real-time streams, scalable compute solutions, and evaluating performance metrics using official documentation and loading strategies to ensure complete domain mastery across complex enterprise cloud storage configurations and ingestion pipelines.

Who Should Take This Exam

Data engineers with advanced experience building and maintaining data pipelines and scalable compute solutions on Snowflake. Candidates should understand data loading, streams, tasks, and cloud storage integrations.

Skills You Should Be Ready to Demonstrate

How to Prepare

Review official Snowflake documentation on Snowpark, Snowpipe, streams, and tasks to ensure full coverage of the core topics. Practice building end-to-end data pipelines and carefully evaluate performance metrics using query profiles and operational dashboards before taking the assessment to guarantee success across all test domains.

Domain Study Guidance

Source data from Data Lakes, APIs, and on-premises: Study Guidance

This domain focuses extensively on sourcing data from various external data lakes, external APIs, and complex on-premises environments directly into Snowflake storage safely and efficiently according to official standards and recommended loading practices.

Transform, replicate, and share data across cloud platforms: Study Guidance

This domain covers transforming, replicating, and securely sharing large volumes of data across different cloud platforms while maintaining governance and structural integrity for modern enterprise analytics platforms and distributed architectures.

Near real-time streams: Study Guidance

This domain involves designing reliable end-to-end near real-time data streams utilizing native ingestion tools and continuous data pipeline mechanisms to handle high-throughput workloads efficiently throughout execution and automated processing cycles.

Scalable compute: Study Guidance

This domain explores designing highly scalable compute solutions specifically tailored for demanding data engineer workloads, ensuring optimal resource allocation and sound cost management during heavy processing tasks across environments.

Performance metrics: Study Guidance

This domain examines how to evaluate specific performance metrics to monitor, troubleshoot, and optimize data pipeline operations and query execution times across your cloud environment successfully based on operational guidelines.

Exam-Day Guidance

Manage your time across the 65 questions effectively, reading prompts carefully and utilizing the available review features for multiple choice, multiple select, and interactive items during the test.

Frequently asked questions

How many questions are on the exam?

The exam consists of 65 questions in total. The question formats include multiple choice, multiple select, and interactive items such as drag and drop and matching exercises.

What is the passing score?

The passing score required to pass the exam is 750, measured on a scaled scoring model determined and maintained by official Snowflake certification standards and policies.

How much does the exam cost?

The exam registration price is $375 USD, which is payable directly through the official Snowflake certification registration platform when you schedule your test appointment with the provider.

What is the official exam code policy?

Check with Snowflake for the current certification path and official exam codes, ensuring you review the proper documentation and preparation guides before scheduling your test.

Sources and Verification

Verified 2026-09-13

How this page was made

This detailed page was built using official Snowflake documentation, official exam guides, and verified facts regarding the advanced certification requirements and associated testing policies.

Exam Domains

1.0 Source data from Data Lakes, APIs, and on-premises Weight not published
  • 1.1Source data from Data Lakes, APIs, and on-premises
2.0 Transform, replicate, and share data across cloud platforms Weight not published
  • 2.1Transform, replicate, and share data across cloud platforms
3.0 Near real-time streams Weight not published
  • 3.1Design end-to-end near real-time streams
4.0 Scalable compute Weight not published
  • 4.1Design scalable compute solutions for Data Engineer workloads
5.0 Performance metrics Weight not published
  • 5.1Evaluate performance metrics

Exam Details

LanguagesEnglish, Japanese