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How long is the SnowPro Specialty: Snowpark (SPS-C01) exam?

The SF-SP exam has 55 questions and a 85-minute time limit.

What is the passing score for SnowPro Specialty: Snowpark (SPS-C01)?

You need 750 / 1000 to pass the SF-SP exam.

What are common mistakes on the SnowPro Specialty: Snowpark (SPS-C01) exam?

Common pitfalls include: Lazy vs Eager Evaluation, Session Object Scope, UDF Types, Snowpark vs PySpark, Stored Procedure Execution. Focus study time on these areas to avoid losing points.

SnowPro Specialty: Snowpark (SPS-C01) Practice Exam 2026 (SF-SP)

Name: Pass-IT
Author: Pass-IT

SnowPro Specialty: Snowpark (SPS-C01)

Validates specialized knowledge of the Snowpark developer framework for Python, including DataFrame API, UDFs, stored procedures, and data transformations. 55+ AI-generated practice questions with explanations. Free trial, pass guarantee.

7-day free trial, no credit card required

55 Questions

85min Time Limit

750/ 1000 Pass Score

$225 USD Exam Fee

About the exam

The SnowPro Specialty: Snowpark Certification (SPS-C01) validates expertise in using the Snowpark API for data engineering and data science on Snowflake, including DataFrame transformations, session management, stored procedures, user-defined functions, and client-side versus server-side result processing. It tests the ability to write production-grade Snowpark code that executes natively within Snowflake's compute environment.

This specialty certification is for data engineers and data scientists with at least one year of hands-on Snowpark experience, advanced Python and PySpark proficiency, and familiarity with Snowflake's execution model. It validates a critical skill set as organizations shift from SQL-only to multi-language data processing on Snowflake.

What's on the exam

The exam consists of 60 questions — multiple-choice and multiple-select — to be completed in 90 minutes. Questions cover domains including DataFrame Operations & Transformations, Session Management & Connectivity, Stored Procedures & UDFs, Action vs Transformation Laziness, and Client-Side vs Server-Side Processing. A passing score is 750 out of 1000. DataFrame API questions dominate — ensure fluency with filter, select, join, groupBy, and agg operations.

Snowpark Concepts 15%

Understand Snowpark architecture, DataFrame API, and session management.

Snowpark API for Python 30%

Use Snowpark Python API for data manipulation, UDFs, stored procedures, and ML integration.

Snowpark for Data Transformations 35%

Build data pipelines and transformations using Snowpark DataFrames, joins, aggregations, and window functions.

Snowpark Performance Optimization 20%

Optimize Snowpark queries, caching, pushdown operations, and warehouse sizing.

Where candidates struggle

Developers who know PySpark but haven't used Snowpark specifically often trip on differences in lazy evaluation behavior, session object patterns, and Snowpark-specific DataFrame methods.

Lazy vs Eager Evaluation — Not understanding which Snowpark operations are lazy (transformations like filter, select) versus eager (actions like collect, show, count) leads to execution order question errors.

Session Object Scope — Misunderstanding Snowpark session lifecycle — how sessions are created, how they map to Snowflake connections, and their thread-safety constraints — causes connectivity question mistakes.

UDF Types — Confusing scalar UDFs, vectorized UDFs (with pandas), and UDTFs (table functions) and not knowing when each is appropriate leads to function design question failures.

Snowpark vs PySpark — Assuming PySpark APIs translate directly to Snowpark and missing Snowpark-specific methods (e.g., merge, copy_into, write_pandas) causes API knowledge question errors.

Stored Procedure Execution — Not understanding that Snowpark stored procedures run inside Snowflake (server-side) with a caller or owner rights model leads to security and execution context mistakes.

Exam logistics

Delivered online via the Snowflake Certification Portal. Available in English. The certification is valid for 2 years. Renewal requires recertification or continuing education credits. Exam fee is $250 USD. Prerequisite: active SnowPro Core certification.

Delivery Online proctored or onsite testing centers.

Retake policy No waiting period between attempts. Full registration fee required for each attempt.

Validity 2 years

Career outcomes Data Engineer, Python Developer, ML Engineer, Snowflake Developer, Data Platform Engineer.

Renewal Pass the current version of the SnowPro Specialty: Snowpark exam to recertify every 2 years.

Study time ~50 hours

Official guide View on vendor site

SnowPro Specialty: Snowpark (SPS-C01)

About the exam

What's on the exam

What to expect

Where candidates struggle

Exam logistics

Ready to pass?