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SnowPro® Advanced: Data Engineer Certification — Requirements & Free Practice

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SnowPro® Advanced: Data Engineer Certification

Validates advanced knowledge and skills used to apply comprehensive data engineering principles using Snowflake.

Licensing authority: Snowflake · Application information

Initial by examination
SnowPro® Advanced: Data Engineer
Certification Requirement
Pass the applicable DEA-C02 Certification Exam under the certification program terms.
Date Applicability
The current official DEA-C02 page and its currently linked DEA-C02 guide support the evaluation date; unpublished official start and end boundaries remain null.
Prerequisite Credential
Eligible individuals must hold an active SnowPro Core credential.
Qualification Boundary
Existing active Core certification is applicant eligibility; no Core examination or credential is newly investigated or produced here.

SnowPro® Advanced: Data Engineer

Provider
Pearson Vue
Format
Multiple Select, Multiple Choice, Interactive; online proctoring or onsite testing centers
Exam questions
Total questions: 65.
Time limit
115 minutes
Passing score
750 + Scaled Scoring from 0 - 1000
Exam fee
$375 USD; India registration fee $300 USD
Examination outline
  • Data Movement (28%)
    • Given a data set, load data into Snowflake.
    • Ingest data of various formats through the mechanics of Snowflake.
    • Troubleshoot data ingestion.
    • Design, build, and troubleshoot continuous data pipelines.
    • Install, configure, and use connectors for Snowflake integration.
    • Design and build data sharing and data consumption solutions.
    • Manage different types of tables and data operations.
  • Performance Optimization (19%)
    • Troubleshoot underperforming queries.
    • Given a scenario, configure a solution for optimal performance.
    • Monitor continuous data pipelines.
  • Storage and Data Protection (14%)
    • Implement and manage data recovery features in Snowflake.
    • Use system functions to analyze micro-partitions.
    • Use Time Travel and cloning to create new development environments.
  • Data Governance (14%)
    • Monitor data.
    • Establish and maintain data protection.
  • Data Transformation (25%)
    • Define User-Defined Functions (UDFs) and outline how to use them.
    • Define and create external functions.
    • Design, build, and leverage stored procedures.
    • Handle and transform semi-structured data.
    • Handle and process unstructured data.
    • Implement and manage development workflows and code management.
    • Use Snowpark for data transformations.
Examination sources