Description

Introduction

The SnowPro® Advanced Data Engineer Recertification Exam Certification Training is designed for professionals looking to renew their SnowPro Advanced Data Engineer Certification. This course provides an in-depth review of Snowflake’s latest data engineering features, performance tuning, data pipeline optimizations, and automation strategies. It ensures that certified data engineers stay up to date with best practices in data modeling, ETL/ELT processes, and scalable architecture within the Snowflake ecosystem.

Prerequisites of SnowPro®

• Valid SnowPro Advanced Data Engineer Certification (or recently expired within the grace period)
• Hands-on experience with Snowflake data engineering workloads
• Familiarity with SQL, ETL/ELT processes, and data pipeline automation
• Understanding of Snowflake’s latest features, performance tuning, and security updates

Table of Contents

1. Snowflake Platform Enhancements for Data Engineering

• 1.1 New Features and Updates Relevant to Data Engineers
• 1.2 Performance and Scalability Enhancements
• 1.3 Best Practices for Adopting New Capabilities

2. Advanced Data Ingestion and Transformation

• 2.1 Optimizing Bulk Data Loads and Continuous Ingestion
• 2.2 Best Practices for ELT with Snowflake
• 2.3 Change Data Capture (CDC) and Streaming Data Pipelines

3. Performance Tuning and Query Optimization

• 3.1 Using Snowflake Query Profile for Debugging Performance Issues
• 3.2 Warehouse Sizing and Auto-Scaling Strategies
• 3.3 Data Clustering, Materialized Views, and Query Acceleration

4. Advanced Data Modeling and Schema Design

• 4.1 Partitioning and Clustering Strategies
• 4.2 Using Snowflake’s Semi-Structured Data Capabilities
• 4.3 Best Practices for Star and Snowflake Schema Implementation

5. Security and Data Governance in Data Engineering

• 5.1 Role-Based Access Control (RBAC) Enhancements for Pipelines
• 5.2 Managing Sensitive Data with Data Masking and Row-Level Security
• 5.3 Auditing and Compliance Best Practices

6. Automation and DevOps for Data Engineering

• 6.1 Using Snowflake APIs for Data Pipeline Automation
• 6.2 Infrastructure as Code (IaC) for Snowflake Pipelines(Ref: SnowPro® Advanced Administrator Recertification Training)
• 6.3 Implementing CI/CD for Data Engineering Workflows

7. Data Sharing and Cross-Cloud Data Movement

• 7.1 Secure Data Sharing Enhancements
• 7.2 Snowflake’s Cross-Region and Cross-Cloud Replication
• 7.3 Managing and Optimizing Data Exchange Between Organizations

8. Troubleshooting and Best Practices for Data Engineers

• 8.1 Debugging ETL/ELT Failures and Performance Bottlenecks
• 8.2 Cost Optimization Strategies for Data Engineering Workloads
• 8.3 Best Practices for Scalable and Secure Data Pipelines

Conclusion

This recertification training equips SnowPro Advanced Data Engineers with updated knowledge of Snowflake’s latest features and best practices. By completing SnowPro® Advanced Data Engineer this course, professionals can maintain their certification, optimize data engineering workflows, enhance performance, and ensure security compliance. Recertification validates expertise and keeps data engineers ahead in the evolving Snowflake data engineering landscape.

Reference