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SnowPro Advanced Data Engineer

Here you have the best Snowflake SnowPro Advanced Data Engineer practice exam questions

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  • These questions were last updated on June 14, 2026
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Question 1 of 162

A Data Engineer is investigating a query that is taking a long time to return. The Query Profile shows the following:

Exam SnowPro Advanced Data Engineer: Question 1 - Image 1

What step should the Engineer take to increase the query performance?

Answer

Suggested Answer

The suggested answer is B.

The query profile indicates that a significant amount of data (37.59 GB) is being spilled to local storage. This is a clear sign that the virtual warehouse does not have enough memory to handle the query efficiently. Spilling to disk is much slower than processing data in memory. To address this, the engineer should increase the size of the virtual warehouse, which will provide more memory and reduce or eliminate the need for disk spilling, thus improving query performance.

Community Votes8 votes
BSuggested
100%
Question 2 of 162

How can the following relational data be transformed into semi-structured data using the LEAST amount of operational overhead?

Exam SnowPro Advanced Data Engineer: Question 2 - Image 1
Answer

Suggested Answer

The suggested answer is C.

To transform relational data into semi-structured data with the least operational overhead, the OBJECT_CONSTRUCT function in Snowflake is an efficient choice. This function constructs a JSON-like output by taking column names and their corresponding values from a table. This operation is simple and direct, avoiding the need for intermediate steps or conversions, making it the least overhead solution among the options provided.

Community Votes11 votes
CSuggested
91%
B
9%
Question 3 of 162

A Data Engineer executes a complex query and wants to make use of Snowflake’s query results caching capabilities to reuse the results.

Which conditions must be met? (Choose three.)

Answer

Suggested Answer

The suggested answer is A, D, E.

To take advantage of Snowflake's query results caching capabilities, the results must be reused within 72 hours. Additionally, the table structure contributing to the query result cannot have changed, and the new query must have the same syntax as the previously executed query. These conditions ensure that the cached results are valid and can be reused efficiently.

Community Votes14 votes
DEFMost voted
71%
BDE
29%
Question 4 of 162

A Data Engineer needs to load JSON output from some software into Snowflake using Snowpipe.

Which recommendations apply to this scenario? (Choose three.)

Answer

Suggested Answer

The suggested answer is B, D, F.

When loading JSON data into Snowflake using Snowpipe, there are specific recommendations to follow for optimal performance and cost efficiency. First, it is recommended to ensure that data files are 100-250 MB or larger in size when compressed, helping to balance performance and cost (option B). Additionally, verifying each value of each unique element stores a single native data type (string or number) ensures data consistency and integrity (option D). Lastly, creating data files less than 100 MB and staging them in cloud storage at a frequency greater than once each minute might seem counterintuitive, but it helps to keep the overhead manageable and avoids issues with latency and queue management in Snowpipe (option F). This combination of practices ensures effective and efficient use of Snowpipe for loading JSON data.

Community Votes6 votes
BDEMost voted
100%
Question 5 of 162

Given the table SALES which has a clustering key of column CLOSED_DATE, which table function will return the average clustering depth for the SALES_REPRESENTATIVE column for the North American region?

Answer

Suggested Answer

The suggested answer is B.

The table function system$clustering_depth is used to return the average clustering depth for a specified set of columns, with an additional optional filter condition. Since the question specifies the need to calculate the average clustering depth for the sales_representative column in the North American region, this function perfectly fits the requirement.

Community Votes2 votes
BSuggested
100%

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