Snowflake - Build and Architect Data Pipelines Using AWS
Data engineering and architecting pipelines using Snowflake and AWS cloud
Created by Siddharth Raghunath
Gain hands-on experience building and architecting data pipelines using Snowflake and AWS. Explore core features of Snowflake, automate workflows, and work with real-time data streaming. Discover how to use Snowpark for data transformation and data science tasks.
Packt | Sep 2022 | 519 min
What You Will Learn
You will work through practical exercises that guide you from Snowflake basics to advanced pipeline architecture. Each section combines clear explanations with hands-on labs, letting you apply new concepts right away. By the end, you will have built end-to-end solutions using Python, PySpark, AWS Glue, Airflow, and Snowpark.
Key Features
- Build automated data pipelines with Snowflake and AWS for scalable data workflows
- Deploy Python and PySpark jobs in AWS Glue and Airflow to transform and manage data
- Work with real-time streaming data using Kafka and integrate Snowpark for advanced analytics
Target Audience
Designed for software engineers, data engineers, analysts, and data scientists with some programming and SQL experience. If you are looking to deepen your skills in cloud-based data engineering and want to build robust, scalable pipelines using Snowflake and AWS, this course will help you reach your goals.
