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SnowPro Advanced: Data Engineer (DEA-C02)

Design, build, optimize, and maintain complex data ingestion, continuous transformation pipelines, streaming architectures, Snowpark development, and performance optimization on Snowflake.

115 min
Time Allowance
52
Exam Questions
75%
Passing Score
~2.2 min
Target Pace / Q

Official Exam Specification & Quick Facts

Certification Track
SnowPro Advanced: Data Engineer (DEA-C02)
Exam Vendor / Provider
Snowflake
Domain Area
Snowflake
Testing Time
115 minutes (~2.2 min/q)
Passing Benchmark
75% scaled score
Simulator Access
100% Free · Unlimited Retakes

Question Difficulty Breakdown

Easy
17 q's (33%)
Medium
18 q's (35%)
Hard
17 q's (33%)
Difficulty distribution mirrors authentic proctored exam questions with scenario traps, multi-select items, and architectural trade-offs.

Exam Guidelines & Simulation Rules

Timed Simulation The 115-minute timer starts immediately. Sessions auto-submit when the clock reaches zero.
Realistic Formats Single-choice and multi-choice scenario questions modeled directly from the official Snowflake syllabus.
Flag & Review Flag challenging questions to review anytime before submitting your final answers.
In-Depth Explanations Instant post-exam breakdown explaining why the correct choice wins and why distractor options fail.

Frequently Asked Questions (FAQ)

The DEA-C02 exam features 65 scenario and advanced coding questions over 115 minutes. Cost is $375 USD with a passing threshold of 750/1000 (75%). SnowPro Core is a required prerequisite.

Domains include: (1) Data Ingestion and Preparation (~25-30%), (2) Data Transformation and Modeling (~25-30%), (3) Data Storage and Security (~20-25%), and (4) Performance and Monitoring (~20-25%).

Standard Snowpipe loads staged files into tables via event notifications. Snowpipe Streaming writes row data directly from applications or Kafka into Snowflake tables via low-latency Java/Python SDKs with sub-second latency.

Dynamic Tables provide a declarative data transformation model. Data engineers write SQL queries defining the target state, and Snowflake automatically schedules incremental refreshes to meet defined lag targets.

Standard streams track all DML changes (inserts, updates, deletes). Append-only streams track only inserts, significantly improving performance for append-only log and event ingestion tables.

Snowpark allows data engineers to write native Python dataframes that compile into optimized SQL executed lazily inside Snowflake's virtual warehouses, with zero data extraction.

The `MATCH_RECOGNIZE` SQL clause enables complex event processing (CEP) by detecting temporal patterns, price trends, or fraud signatures across sequences of ordered rows.

Vector data types allow storing and indexing mathematical embeddings directly in Snowflake tables, powering semantic search and retrieval-augmented generation (RAG) pipelines.

The Query Profile visualizes execution stages, identifying expensive table scans, percentage of partitions pruned, join Cartesian explosions, and disk spilling (local vs remote).

External tables are read-only views over files. Apache Iceberg tables in Snowflake provide full ACID transactional read/write capabilities over open Parquet tables stored in customer-managed S3/Azure buckets.

The DEA-C02 credential is valid for two years from the pass date.

DEA-C02 certifies Senior Data Engineers, Cloud Analytics Engineers, and Pipeline Developers earning average US salaries between $140,000 and $185,000.