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Snowflake DEA-C01 Exam Overview:
| Certification Vendor: | Snowflake |
|---|---|
| Exam Name: | SnowPro Advanced: Data Engineer Certification Exam |
| Exam Number: | DEA-C01 |
| Real Exam Qty: | 65 |
| Exam Duration: | 115 minutes |
| Available Languages: | Japanese, English |
| Related Certifications: | SnowPro Advanced: Data Analyst SnowPro Core SnowPro Advanced: Data Scientist SnowPro Advanced: Architect SnowPro Advanced: Administrator SnowPro Advanced: Security Engineer |
| Passing Score: | 750 / 1000 |
| Exam Format: | Multiple choice, Multiple select |
| Exam Price: | $375 USD |
| Certificate Validity Period: | 2 years |
| Recommended Training: | SnowPro Advanced: Data Engineer Exam Study Guide Snowflake University Training Courses |
| Exam Registration: | Pearson VUE Registration Snowflake Certification Portal |
| Sample Questions: |  |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Must hold active SnowPro Core Certification; recommended 2+ years hands-on data engineering experience |
| Official Syllabus URL: | https://learn.snowflake.com/en/certifications/snowpro-advanced-dataengineer/ |
Snowflake DEA-C01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Governance, Security & Sharing | 10% | - Share data securely across accounts and platforms - Apply access control, masking, encryption, and compliance - Track lineage, audit, and maintain data integrity |
| Data Transformation & Processing | 30% | - Use streams, tasks, dynamic tables for pipelines and CDC - Work with semi-structured and unstructured data - Implement data quality, validation, and schema evolution - Design and implement transformations: SQL, stored procedures, user-defined functions |
| Data Pipeline Orchestration & Automation | 20% | - Error handling, retry logic, and dependency management - Build, schedule, monitor, and manage workflows - Integrate with external orchestration tools |
| Performance Optimization & Scalability | 15% | - Design scalable compute and storage solutions - Monitor and tune workloads and resource usage - Optimize warehouses, clustering, partitioning, and query performance |
| Data Ingestion | 25% | - Handle file formats, compression, encoding, and schema detection - Use COPY INTO, external tables, Snowpipe, Snowpipe Streaming - Ingest from various sources: cloud storage, on-premises, APIs, data lakes |
DEA-C01 Exam Questions and Study Options
Whichever matches your habits — all three are built around the same Snowflake SnowPro Advanced: Data Engineer Certification content. The PDF version suits paper readers: print it out, mark it up, and share pages with a study partner. The PC test engine suits computer-based learners: it simulates the real exam scene, lets you set a time limit like the live DEA-C01 exam, flags your mistakes, and reminds you to re-practice them daily. The online APP includes every software function and runs on Windows, Mac, Android, and iOS. Choose the one you will actually use every day.
The DEA-C01 exam contains 65 questions to be completed in 115 minutes minutes. That pace is exactly what the PC test engine's timed mode trains — set the same limit in practice, and the real clock stops being a surprise.
Snowflake recommends these training options for candidates:
Official courses build understanding; a daily practice routine with expert-verified answers builds exam-day readiness. The strongest preparation uses both.
To pass the DEA-C01 exam you need 750 / 1000, and registration costs $375 USD. Set against that fee, thorough preparation is the smaller expense by far — and the one most likely to protect the larger one.
The official outline divides the DEA-C01 exam into weighted domains, including:
- Performance Optimization & Scalability (15%)
- Data Transformation & Processing (30%)
- Data Pipeline Orchestration & Automation (20%)
The Snowflake SnowPro Advanced: Data Engineer Certification practice questions at PassCollection follow these same objectives, whichever of the three study formats you use.
Yes. We understand that many candidates prefer not to advertise how they prepare. PassCollection runs a strict information protection system: your personal details and your DEA-C01 exam purchase are kept secret and safe, and never disclosed to any third party. You can order the Snowflake SnowPro Advanced: Data Engineer Certification materials with complete peace of mind.
Must hold active SnowPro Core Certification; recommended 2+ years hands-on data engineering experience
The DEA-C01 exam is the official assessment behind the Snowflake SnowPro Advanced: Data Engineer Certification certification from Snowflake. Many IT professionals pursue it as a step toward leadership roles, because the credential verifies practical command of the published objectives. Solid preparation — not luck — is what carries candidates through it.
You can register for the DEA-C01 exam through these official channels:
Book your seat only when your timed practice scores say you are ready — the registration fee is better paid once than twice.
Snowflake SnowPro Advanced: Data Engineer Certification Sample Questions:
A company receives call logs as Amazon S3 objects that contain sensitive customer information.
The company must protect the S3 objects by using encryption. The company must also use encryption keys that only specific employees can access.
Which solution will meet these requirements with the LEAST effort?
- A. Use server-side encryption with customer-provided keys (SSE-C) to encrypt the objects that contain customer information. Restrict access to the keys that encrypt the objects.
- B. Use an AWS CloudHSM cluster to store the encryption keys. Configure the process that writes to Amazon S3 to make calls to CloudHSM to encrypt and decrypt the objects. Deploy an IAM policy that restricts access to the CloudHSM cluster.
- C. Use server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the KMS keys that encrypt the objects.
- D. Use server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the Amazon S3 managed keys that encrypt the objects.
Correct Answer: C 🗳️
A company has implemented a lake house architecture in Amazon Redshift. The company needs to give users the ability to authenticate into Redshift query editor by using a third-party identity provider (IdP).
A data engineer must set up the authentication mechanism.
What is the first step the data engineer should take to meet this requirement?
- A. Register the third-party IdP as an identity provider in the configuration settings of the Redshift cluster.
- B. Register the third-party IdP as an identity provider from within Amazon Redshift.
- C. Register the third-party IdP as an identity provider for AVS Secrets Manager. Configure Amazon Redshift to use Secrets Manager to manage user credentials.
- D. Register the third-party IdP as an identity provider for AWS Certificate Manager (ACM). Configure Amazon Redshift to use ACM to manage user credentials.
Correct Answer: A 🗳️
Explanation: Only visible for PassCollection members. You can sign-up / login (it's free).
A company receives a data file from a partner each day in an Amazon S3 bucket. The company uses a daily AWS Glue extract, transform, and load (ETL) pipeline to clean and transform each data file. The output of the ETL pipeline is written to a CSV file named Daily.csv in a second S3 bucket.
Occasionally, the daily data file is empty or is missing values for required fields. When the file is missing data, the company can use the previous day's CSV file.
A data engineer needs to ensure that the previous day's data file is overwritten only if the new daily file is complete and valid.
Which solution will meet these requirements with the LEAST effort?
- A. Run a SQL query in Amazon Athena to read the CSV file and drop missing rows. Copy the corrected CSV file to the second S3 bucket.
- B. Configure the AWS Glue ETL pipeline to use AWS Glue Data Quality rules. Develop rules in Data Quality Definition Language (DQDL) to check for missing values in required fields and empty files.
- C. Invoke an AWS Lambda function to check the file for missing data and to fill in missing values in required fields.
- D. Use AWS Glue Studio to change the code in the ETL pipeline to fill in any missing values in the required fields with the most common values for each field.
Correct Answer: B 🗳️
Explanation: Only visible for PassCollection members. You can sign-up / login (it's free).
A company needs to generate a one-time performance report by joining data that is stored in Amazon DynamoDB. Amazon RDS. Amazon Redshift. and Amazon S3. The company wants to avoid unnecessary data movement and to minimize query execution time. Which solution will meet these requirements?
- A. Capture data from DynamoDB by using DynamoDB Streams. Migrate data from Amazon RDS by using AWS DMS. Export Amazon Redshift data. Store all data in Amazon S3. Use Redshift Spectrum to run queries.
- B. Set up an AWS Glue ETL pipeline to extract, transform, and centralize data in Amazon S3. Use Amazon Athena to run analytical queries.
- C. Use Amazon Athena Federated Query to perform one-time joins and analysis across DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.
- D. Deploy an Amazon EMR cluster powered by Apache Spark to ingest, process, and merge datasets from multiple sources. Run analytical workloads on the merged data.
Correct Answer: C 🗳️
Explanation: Only visible for PassCollection members. You can sign-up / login (it's free).
A sales company uses AWS Glue ETL to collect, process, and ingest data into an Amazon S3 bucket. The AWS Glue pipeline creates a new file in the S3 bucket every hour. File sizes vary from 200 KB to 300 KB. The company wants to build a sales prediction model by using data from the previous 5 years. The historic data includes 44,000 files.
The company builds a second AWS Glue ETL pipeline by using the smallest worker type. The second pipeline retrieves the historic files from the S3 bucket and processes the files for downstream analysis. The company notices significant performance issues with the second ETL pipeline.
The company needs to improve the performance of the second pipeline.
Which solution will meet this requirement MOST cost-effectively?
- A. Increase the number of workers in the AWS Glue ETL jobs.
- B. Use the AWS Glue DynamicFrame grouping option.
- C. Enable AWS Glue auto scaling.
- D. Use a larger worker type.
Correct Answer: B 🗳️
Explanation: Only visible for PassCollection members. You can sign-up / login (it's free).
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