Snowflake DEA-C02 Exam Information and Actual Questions

  • Exam Code/Number: DEA-C02
  • Exam Name/Title: SnowPro Advanced: Data Engineer (DEA-C02)
  • Certification Provider: Snowflake
  • Corresponding Certification: SnowPro Advanced
  • Exam Questions: 354
  • Updated On: Jun 30, 2026

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

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Snowflake DEA-C02 Exam Overview:

Certification Vendor:Snowflake
Exam Name:SnowPro Advanced: Data Engineer
Exam Number:DEA-C02
Real Exam Qty:100
Passing Score:70%
Available Languages:English
Exam Price:$350 USD
Exam Format:Multiple Choice, Multiple Select
Exam Duration:115 minutes
Certificate Validity Period:2 years
Related Certifications:SnowPro Core
SnowPro Data Scientist
SnowPro Architect
Sample Questions:Snowflake DEA-C02 Sample Questions
Exam Way:Online proctored exam
Pre Condition:Recommended: SnowPro Core certification or equivalent hands-on experience with Snowflake
Official Syllabus URL:https://www.snowflake.com/certification/

Snowflake DEA-C02 Exam Syllabus Topics:

SectionWeightObjectives
Security and Governance15%- Access Control
  • 1. Role hierarchy and ownership
  • 2. GRANT and REVOKE operations
  • 3. Role-based access control (RBAC)
- Data Security
  • 1. Row-level security policies
  • 2. External tokenization
  • 3. Column-level security
  • 4. Data masking and tokenization
- Governance and Compliance
  • 1. Access history and auditing
  • 2. Row access policies
  • 3. Object tagging
  • 4. Data retention policies
Data Architecture and Processing20%- Data Modeling for Performance
  • 1. Dimension handling
  • 2. Star and snowflake schemas
  • 3. Slowly changing dimensions (SCD)
- Data Storage Architecture
  • 1. Hybrid Tables concepts
  • 2. Micro-partitioning and clustering
  • 3. Table types (Permanent, Transient, Temporary)
- Data Pipeline Design
  • 1. Data scheduling and orchestration
  • 2. Pipeline monitoring and error handling
  • 3. Stream and task patterns
Performance Optimization15%- Query Optimization
  • 1. Query result caching
  • 2. Avoiding common performance pitfalls
  • 3. Indexing strategies with clustering
  • 4. Query profiling and analysis
- Warehouse Performance
  • 1. Multi-cluster warehouses
  • 2. Warehouse sizing and selection
  • 3. Warehouse scaling policies
  • 4. Resource monitors
- Data Optimization
  • 1. Search optimization service
  • 2. Materialized views
  • 3. Data cache management
Data Transformation with Snowflake30%- Data Processing Patterns
  • 1. Time travel and change data capture
  • 2. MERGE, UPDATE, DELETE operations
  • 3. Zero-copy cloning for ETL
- SQL Transformations
  • 1. Complex JOINs and set operations
  • 2. Window functions advanced usage
  • 3. Data type conversions and handling
  • 4. Working with semi-structured data (VARIANT)
- Snowflake Scripting
  • 1. Error handling
  • 2. Procedures and control flow
  • 3. Dynamic SQL
Data Ingestion and Consumption20%- Bulk Loading and Unloading
  • 1. COPY INTO command options and best practices
  • 2. File format options (CSV, JSON, Parquet, AVRO)
  • 3. Data loading performance optimization
  • 4. Handling staged files
- Continuous Data Loading
  • 1. Automating data loading with tasks
  • 2. Snowpipe configuration and usage
  • 3. Real-time data ingestion patterns
- Data Unloading
  • 1. Partitioning unloading data
  • 2. Unloading to internal and external stages
  • 3. Data export best practices


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