Overview

This three-day role-specific course covers key concepts, features, considerations, and Snowflake recommended best practices through the lens of the data engineering workflow. It is intended for participants who will be accessing, developing, and querying datasets for analytic tasks and building data pipelines in Snowflake. This course consists of core data engineering concepts delivered through lectures, demos, labs, and discussions.

Skills Covered

  • Describe the data engineering workflow and how the Snowflake AI Data Cloud features support the various components of the workflow.
  • Access Snowflake through the Snowsight UI and by using application methods.
  • Load and unload data sets.
  • Configure Snowflake features to cover a range of data ingestion and processing latencies.
  • Develop applications for Snowflake, including comprehensive ANSI standard SQL support.
  • Employ performance and cost optimization techniques.
  • Use Snowflake’s capabilities to work effectively with structured, semi-structured, and unstructured data in Snowflake.
  • Tune queries and improve performance using advanced techniques such as data clustering and materialized views.
  • Employ Snowflake SQL extensibility features such as user-defined functions and stored procedures.

Prerequisites

  • Recommended completion of the “Snowflake Multi-Factor Authentication (MFA) Essentials” free on-demand course.
  • Completion of “Snowflake Foundations” one-day course or equivalent Snowflake knowledge.
  • A background in data engineering is required.

Target Audience

  • Data Analysts
  • Data Engineers
  • Data Scientists
  • Database Architects
  • Database Administrators
  • Data Application Developers

Course Curriculum

Module 1: Snowflake AI Data Cloud
Module 2: Introduction to the Data Engineering Workflow
Module 3: Supporting Platform Features

  • Authentication Methods
  • Drivers, Clients, and Connectors Overview
  • Role-based Access Control (RBAC) Overview
  • Introduction to Data Governance
  • QueryTags

Module 4: Data Storage

  • Semi-structured Data
  • QuerySemi-structured Data
  • Data Lake
  • Apache Iceberg™ Tables
  • External Tables

Module 5: Ingestion

  • Bulk vs. Continuous Data Loading Approaches
  • Snowpipe
  • Snowpipe Streaming
  • Snowflake Connector for Kafka
  • Snowflake Connector for Kafka with Snowpipe Streaming
  • Snowflake Data Loading Best Practices
  • Loading Semi-structured Data
  • SchemaDetection
  • Working with Unstructured Data

Module 6: Transformation

  • Extensibility Overview
  • Snowflake Scripting
  • UDFsandUDTFs
  • Extend Snowflake with Java and Python
  • External Functions
  • External Network Access
  • Data Sharing
  • Introduction to Snowpark
  • Working with Snowflake Notebooks
  • Transformations with Unstructured Data

Module 7: Powering Data with Snowflake LLMs

  • Document AI
  • Cortex LLM Functions Overview
  • Cortex LLM Task-specific Functions
  • Cortex LLM Complete Functions
  • Cost Monitoring

Module 8: Orchestration

  • Creating and Managing Tasks
  • Creating and Managing Streams
  • Streams on Views
  • Using Streams and Tasks Together
  • Dynamic Tables

Module 9: Performance Optimization

  • Natural Clustering
  • Explicit Clustering
  • Automatic Clustering Service
  • Search Optimization Service
  • SQLPerformance Tips
  • Performance Bottleneck Scenarios

Module 10: Delivery

  • Materialized Views
  • Unloading Semi-structured Data
  • Secure Views

Module 11: Management and Observability

  • Observability on Snowflake
  • Outbound Notifications
  • Snowflake Alerts
  • Data Metric Functions
  • System DMF
  • CustomDMF
  • Observability Within Snowsight
  • Cost Controls
  • Resource Monitors

Dates & Locations

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Trainocate exam and cert

Exam & Certification

The SnowPro® Advanced: Data Engineer Certification DEA-C02.

SNOWPRO ADVANCED: DATA ENGINEER OVERVIEW

This certification will test the ability to:

  • Source data from Data Lakes, APIs, and on-premises
  • Transform, replicate, and share data across cloud platforms
  • Design end-to-end near real-time streams
  • Design scalable compute solutions for Data Engineer workloads
  • Evaluate performance metrics

Training & Certification Guide

Exam Version: DEA-C02
Total Number of Questions: 65
Question Types: Multiple Select, Multiple Choice, Interactive
Time Limit: 115 minutes
Language: English
Registration fee: $375 USD
India Registration fee: $300 USD
Passing Score: 750 + Scaled Scoring from 0 – 1000
Unscored Content: Exams may include unscored items to gather statistical information for future use. These items are not identified on the form and do not impact your score, and additional time is factored into account for this content.

Prerequisites: SnowPro Core Certified
Delivery Options:

  • 1: Online Proctoring
  • 2: Onsite Testing Centers

EXAM DOMAIN BREAKDOWN

The table below lists the main content domains and their weightings.

Domain Domain Weightings
1.0 Data Movement 26%
2.0 Performance Optimization 21%
3.0 Storage and Data Protection 14%
4.0 Data Governance 14%
5.0 Data Transformation 25%

RECOMMENDED TRAINING

As preparation for this exam, we recommend a combination of hands-on experience, instructor-led training, and the utilization of self-study assets.

Instructor-Led Course recommended for this exam:

Snowflake Data Engineer Training

Register for the Snowflake Practice Exam now:

SnowPro Practice Exam: Data Engineer

Frequently Asked Questions

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