Spark, Hadoop, and Snowflake for Data Engineering
Completed by Felix Schneider-Soupiadis
January 13, 2026
29 hours (approximately)
Felix Schneider-Soupiadis'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 Quality
- Category: Model Deployment
- Category: Snowflake Schema
- Category: DevOps
- Category: PySpark
- Category: Data Processing
- Category: Data Integration
- Category: Data Transformation
- Category: MLOps (Machine Learning Operations)
- Category: Python Programming
- Category: Data Pipelines
- Category: Big Data
