Snowflake · Professional
Snowflake SnowPro Advanced: Data Engineer (DEA-C02)
Build and optimize production data pipelines in Snowflake with Streams, Tasks, Dynamic Tables, and Snowpark.
DEA-C02 exam at a glance
| Exam code | DEA-C02 |
|---|---|
| Vendor | Snowflake |
| Level | Professional |
| Domains | 5 |
| Published practice questions | 262 |
| Our mock exam | 65 questions in 115 minutes |
| Our practice pass target | 75% |
| Checked against the exam guide | September 22, 2026 |
| Official exam page | Snowflake — DEA-C02 |
The mock exam length, time limit and pass target are our practice settings, not official exam scores or a guarantee of passing. Check the official DEA-C02 exam page for the current format, price and scoring before you book.
DEA-C02 exam domains
Weights show our practice allocation, built from the official exam guide; official blueprints may give ranges. Each domain links to its free sample questions (with explanations) and study guide preview once they are published.
Data Movement
27%Design and implement production data ingestion pipelines using Snowflake's native batch, streaming, and orchestration capabilities.
- COPY INTO: file formats (CSV, JSON, Parquet, ORC, Avro), COPY options, error handling
- Snowpipe: auto-ingest with S3/Azure/GCS event notifications, REST API ingestion
- Snowpipe Streaming: low-latency row-level ingestion, Kafka connector, SDK
- Streams: standard, append-only, and insert-only streams, CHANGES clause
- Tasks: scheduling, task graphs (DAGs), serverless tasks, error notifications
- Dynamic Tables: declarative pipelines, incremental refresh, lag monitoring
- External stages: S3, Azure Blob, GCS configuration, storage integrations
- Kafka Connector for Snowflake: configuration, schema registry, offset management
- GET and PUT commands: internal stages, table stages, user stages
Free Data Movement practice questions →Data Movement study guide →
Data Transformation
25%Transform loaded data inside Snowflake using SQL, procedural code, and semi-structured data functions.
- Data transformation patterns: ELT in Snowflake SQL, window functions, MERGE
- Data format conversion: PARSE_JSON, TRY_CAST, FLATTEN for semi-structured data
- dbt with Snowflake: incremental models, snapshots, best practices
- Stored procedures (SQL, JavaScript, Python/Snowpark) for transformation logic
- User-defined functions and table functions (UDFs/UDTFs) in transformation pipelines
- Snowpark DataFrame API for Python/Scala/Java transformations
- Views and materialized views as transformation layers
- Transaction management: BEGIN, COMMIT, ROLLBACK in multi-step transformations
Free Data Transformation practice questions →Data Transformation study guide →
Performance Optimization
20%Diagnose query performance issues, optimize warehouse utilization, and tune Snowflake data pipelines.
- Query profile: understanding operator nodes, partition pruning stats, spilling to disk
- EXPLAIN plan: interpreting execution plans, identifying bottlenecks
- Micro-partition pruning: metadata-only queries, clustering effectiveness, SYSTEM$CLUSTERING_DEPTH
- Result cache: when it applies, invalidation triggers, forcing re-execution
- Warehouse cache (SSD): warming strategies, cache eviction, resize impact
- Skewed data: detection via QUERY_HISTORY, partition imbalance remediation
- JOIN optimization: join type selection, filter pushdown, anti-joins
- COPY INTO troubleshooting: VALIDATE, LOAD_HISTORY, COPY_HISTORY views
- Task and Stream troubleshooting: TASK_HISTORY, STREAM_STALE, offset monitoring
- Snowpipe error investigation: PIPE_USAGE_HISTORY, COPY_HISTORY, error tables
- INFORMATION_SCHEMA and ACCOUNT_USAGE: performance monitoring queries
- Query tagging and labelling for performance attribution
Free Performance Optimization practice questions →Performance Optimization study guide →
Storage and Data Protection
14%Implement data protection strategies using Time Travel, Fail-safe, replication, and encryption in Snowflake.
- Time Travel: DATA_RETENTION_TIME_IN_DAYS, AT and BEFORE syntax, UNDROP
- Fail-safe: 7-day non-configurable recovery period, Snowflake-only access
- Cloning: zero-copy clones of tables, schemas, databases — use cases and storage
- Data replication: primary and secondary databases, REPLICATION GROUP, failover
- Cross-account and cross-cloud replication: network policies, latency considerations
- Table types and storage cost: permanent vs transient vs temporary
- Compression: automatic compression, SHOW TABLES storage statistics
- External tables: data remains in cloud storage, metadata in Snowflake
- Iceberg Tables: open table format, catalog integration, read/write performance
- Backup and recovery patterns: combination of cloning, replication, and Time Travel
- Delta sharing: open protocol for cross-platform data sharing
Free Storage and Data Protection practice questions →Storage and Data Protection study guide →
Data Governance
14%Implement authentication, authorization, network controls, and data governance for Snowflake data engineering pipelines.
- Service account authentication: key-pair auth, key rotation, OAuth for programmatic access
- Role hierarchy for pipelines: dedicated ETL roles, least privilege principle
- Object ownership and future grants: GRANT FUTURE PRIVILEGES
- Network policies: IP allowlisting for pipeline servers, private link integration
- Dynamic data masking in pipeline outputs: masking policies on stage tables
- Row access policies for multi-tenant pipelines
- Object tagging and classification for governance and discovery
- Column-level security: masking policies with conditional unmasking
- Secure views and secure UDFs: preventing data exposure in data products
- Audit: QUERY_HISTORY, ACCESS_HISTORY for pipeline compliance tracking
Free Data Governance practice questions →Data Governance study guide →
DEA-C02 FAQ
How is the SnowPro Advanced: Data Engineer (DEA-C02) practice assessment configured?
Our practice format targets 65 questions in 115 minutes. Availability depends on the published question bank and is shown on this course page. Official exam question counts and formats may differ.
What does the 75% practice target mean?
Check the provider's current exam guide for official scoring. A practice percentage is not an official scaled score. DataCertPrep uses 75% as an internal practice target, not a prediction or guarantee of passing.
How should I assess my progress in SnowPro Advanced: Data Engineer (DEA-C02)?
Use practice accuracy to find weak topics. Repeating familiar questions can inflate your score. Check coverage of the current objectives, practise hands-on tasks, and assess yourself on unseen questions.
What is the best way to study SnowPro Advanced: Data Engineer (DEA-C02)?
Read the available guides, work through practice explanations, use flashcards and complete practical exercises. Take a timed assessment when available. Check the provider's current exam guide before booking your exam.
Should I use DEA-C02 exam dumps?
No. "Dumps" are questions copied or recalled from the live exam. Certification exams are covered by a candidate agreement that prohibits sharing or using them, and breaking it can lead to a revoked certification or a ban from future exams. Dumps are also often wrong, and they go out of date when the exam blueprint changes. Memorising answers does not build the skills the exam tests. Study the official Snowflake exam guide and practise with original questions that explain each answer, such as the free sample questions linked on this page.