Study with Snowflake : DEA-C01 Exam Torrent as your best preparation materials

Last Updated: Oct 09, 2026

No. of Questions: 387 Questions & Answers with Testing Engine

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Snowflake DEA-C01 Practice Q&A's

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Reading on a phone during a commute, printing pages for notes and marks, or running an interactive simulator on a PC: the three Snowflake SnowPro Advanced: Data Engineer Certification formats on SurePassExams cover all of these DEA-C01 study styles.

Snowflake DEA-C01 Exam Overview:

Certification Vendor:Snowflake
Exam Name:SnowPro Advanced: Data Engineer Certification Exam
Exam Number:DEA-C01
Real Exam Qty:Approximately 65 questions
Available Languages:English
Passing Score:Not publicly disclosed (Snowflake uses scaled scoring)
Certificate Validity Period:2 years
Exam Duration:115 minutes
Exam Format:Multiple choice, Scenario-based questions, Multiple select
Related Certifications:SnowPro Core Certification
Exam Price:$375 USD
Recommended Training:Snowflake University Training
SnowPro Advanced Data Engineer Exam Guide
Exam Registration:Snowflake Certification Portal
Sample Questions: DOWNLOAD DEMO
Exam Way:Online proctored or authorized testing center
Pre Condition:Recommended: SnowPro Core Certification or equivalent Snowflake experience
Official Syllabus URL:https://www.snowflake.com/certifications/snowpro-advanced-data-engineer/

Snowflake DEA-C01 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Engineering Fundamentals on Snowflake- Data ingestion concepts
  • 1. Batch loading strategies
    • 2. Continuous ingestion concepts
      - Snowflake architecture for data engineering
      • 1. Storage and compute separation
        • 2. Virtual warehouses and compute scaling
          Topic 2: Performance Optimization- Query performance tuning
          • 1. Caching mechanisms
            • 2. Clustering and micro-partitions
              - Warehouse optimization
              • 1. Concurrency management
                • 2. Scaling strategies
                  Topic 3: Semi-Structured and Advanced Data Handling- Semi-structured data processing
                  • 1. VARIANT data type usage
                    • 2. JSON, Avro, Parquet handling
                      - Advanced transformation techniques
                      • 1. Flattening nested data
                        • 2. Complex transformations in SQL
                          Topic 4: Data Pipelines and Transformation- ETL/ELT design patterns in Snowflake
                          • 1. Staging and transformation layers
                            • 2. Data orchestration concepts
                              - Streams and Tasks
                              • 1. Change Data Capture (CDC) with Streams
                                • 2. Automating pipelines with Tasks
                                  Topic 5: Data Loading and Integration- Snowpipe and continuous ingestion
                                  • 1. Automated ingestion workflows
                                    • 2. Event-driven loading
                                      - Bulk data loading
                                      • 1. COPY INTO command usage
                                        • 2. File format handling
                                          Topic 6: Security, Governance, and Data Sharing- Access control
                                          • 1. Role-based access control (RBAC)
                                            • 2. Object-level permissions
                                              - Data governance
                                              • 1. Secure data sharing concepts
                                                • 2. Data masking policies

                                                  Snowflake SnowPro Advanced: Data Engineer Certification: What Candidates Ask

                                                  Snowflake Certification Portal: register for DEA-C01

                                                  The package includes 387 practice questions for the DEA-C01 exam, all with verified answers. The same content is available in three formats, so you can switch freely.

                                                  The DEA-C01 exam contains Approximately 65 questions questions to complete within 115 minutes minutes. Rehearsing under the same limit on the simulator builds calm, automatic pacing.

                                                  The PDF reads on phones, tablets, and computers, and it prints cleanly for candidates who like marking notes on paper. The PC file is an interactive simulator that makes rehearsal engaging. The online file is the updated edition of the PC version: intelligent functions, real-test simulation, and no limit on installation devices. All three carry the same questions and answers.

                                                  Recommended: SnowPro Core Certification or equivalent Snowflake experience

                                                  • Semi-Structured and Advanced Data Handling ()
                                                  • Data Loading and Integration ()
                                                  • Security, Governance, and Data Sharing ()

                                                  Plan your hours according to each topic's weight.

                                                  DEA-C01 requires Not publicly disclosed (Snowflake uses scaled scoring) to pass, and the official exam fee is $375 USD. Fixing both numbers early keeps your practice target and your budget on the same page.

                                                  Before you buy, our team answers any question about the Snowflake SnowPro Advanced: Data Engineer Certification material, and the free demo lets you test it. After payment, the files reach your email within seconds, updates follow by email whenever the exam changes, and we protect your personal information throughout. Promotions appear on our homepage from time to time, so regular visitors often buy at a better price.

                                                  Snowflake SnowPro Advanced: Data Engineer Certification Sample Questions:

                                                  Question #1

                                                  A company is using Amazon S3 to build a data lake. The company needs to replicate records from multiple source databases into Apache Parquet format.
                                                  Most of the source databases are hosted on Amazon RDS. However, one source database is an on-premises Microsoft SQL Server Enterprise instance. The company needs to implement a solution to replicate existing data from all source databases and all future changes to the target S3 data lake.
                                                  Which solution will meet these requirements MOST cost-effectively?

                                                  • A. Use AWS Glue jobs to replicate existing data. Use Amazon Kinesis Data Streams to replicate future changes.
                                                  • B. Use one AWS Glue job to replicate existing data. Use a second AWS Glue job to replicate future changes.
                                                  • C. Use AWS Database Migration Service (AWS DMS) to replicate existing data. Use AWS Glue jobs to replicate future changes.
                                                  • D. Use AWS Database Migration Service (AWS DMS) to replicate existing data and future changes.
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: D  🗳️

                                                  Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).

                                                  Question #2

                                                  A company runs an Apache Spark application every night in an Amazon EMR cluster. The company uses Amazon EC2 instances to supply compute capacity for the EMR cluster. The company deployed the Spark application in cluster mode.
                                                  An error occurs in the Spark application. A log for the error is stored in the application's Spark driver standard error logs. A data engineer needs to investigate the error.
                                                  Where can the data engineer find this error log?

                                                  • A. The engineer can connect to the web UI on the live cluster to see the YARN ResourceManager logs.
                                                  • B. The engineer can connect to the primary node of the cluster by using SSH to see the Spark history server logs.
                                                  • C. The engineer can connect to the Amazon EMR console to see the Amazon EMR step logs that are archived in Amazon S3.
                                                  • D. The engineer can connect to the persistent application UI to see the first YARN container log in the Spark UI.
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: C  🗳️

                                                  Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).

                                                  Question #3

                                                  A company needs to build an extract, transform, and load (ETL) pipeline that has separate stages for batch data ingestion, transformation, and storage. The pipeline must store the transformed data in an Amazon S3 bucket. Each stage must automatically retry failures. The pipeline must provide visibility into the success or failure of individual stages.
                                                  Which solution will meet these requirements with the LEAST operational overhead?

                                                  • A. Chain AWS Glue jobs that perform each stage together by using job triggers. Set the MaxRetries field to 0.
                                                  • B. Schedule Apache Airflow directed acyclic graphs (DAGs) on Amazon Manages Workflows tor Apache Airflow (Amazon MWAA) to orchestrate pipeline steps. Use Amazon Simple Queue Service (Amazon SQS) to ingest data. Use AWS Glue jobs to transform data and store the data in the S3 bucket.
                                                  • C. Build an Amazon EventBridge based pipeline that invokes AWS Lambda functions to perform each stage.
                                                  • D. Deploy AWS Step Functions workflows to orchestrate AWS Lambda functions that ingest data.
                                                    Use AWS Glue jobs to transform the data and store the data in the S3 bucket.
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: D  🗳️

                                                  Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).

                                                  Question #4

                                                  A data engineer needs a fully automated solution to check for new data in multiple databases and process data that the solution finds. The solution must run every hour. The solution must be compatible with Amazon RDS, Amazon DynamoDB, and Amazon OpenSearch Service. The solution must be able to process up to 10 MB of data at one time. The solution must be optimized for costs and operational overhead. The solution must have robust error handling capabilities.
                                                  Which solution will meet these requirements?

                                                  • A. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to create a workflow that runs a directed acyclic graph (DAG) every hour to check for data. Configure the DAG to process identified data. Implement error handling in a Python operator.
                                                  • B. Use Amazon EventBridge to invoke an AWS Lambda function every hour to check for data.
                                                    Configure the function to send a message to an Amazon Simple Queue Service (Amazon SQS) queue when the function finds new data. Use a second Lambda function to read the queue and perform the processing.
                                                  • C. Configure an Apache Spark application to run on Amazon EMR to check for data. Implement error handling in the application. Use Amazon EventBridge to invoke the application every hour.
                                                  • D. Use Amazon EventBridge to invoke AWS Step Functions every hour to deploy an AWS Lambda function to check for data. Configure Step Functions steps to process data that the Lambda function finds. Implement error handling in each state.
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: D  🗳️

                                                  Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).

                                                  Question #5

                                                  A media company wants to improve a system that recommends media content to customer based on user behavior and preferences. To improve the recommendation system, the company needs to incorporate insights from third-party datasets into the company's existing analytics platform.
                                                  The company wants to minimize the effort and time required to incorporate third-party datasets.
                                                  Which solution will meet these requirements with the LEAST operational overhead?

                                                  • A. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories.
                                                  • B. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).
                                                  • C. Use API calls to access and integrate third-party datasets from AWS Data Exchange.
                                                  • D. Use API calls to access and integrate third-party datasets from AWS DataSync.
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: D  🗳️

                                                  Explanation: Only visible for SurePassExams members. You can sign-up / login (it's free).

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