Spark, Hadoop, and Snowflake for Data Engineering
Completed by Marcos Custodio
April 21, 2026
29 hours (approximately)
Marcos Custodio's account is verified. Coursera certifies their successful completion of Spark, Hadoop, and Snowflake for Data Engineering
What you will learn
Create scalable data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data handling.
Optimize data engineering with clustering and scaling to boost performance and resource use.
Build ML solutions (PySpark, MLFlow) on Databricks for seamless model development and deployment.
Implement DataOps and DevOps practices for continuous integration and deployment (CI/CD) of data-driven applications, including automating processes.
Skills you will gain
- Category: Data Integration
- Category: PySpark
- Category: SQL
- Category: Data Pipelines
- Category: Data Processing
- Category: Snowflake Schema
- Category: DevOps
- Category: Data Warehousing
- Category: Distributed Computing
- Category: Databricks
- Category: MLOps (Machine Learning Operations)
- Category: Data Architecture
