Data Engineering Bootcamp – Series 1

Source: https://www.udemy.com/course/data-engineering-bootcamp-series-1/

What you’ll learn

• Understand the Fundamentals of Modern Data Engineering
• Build and Manage Scalable Data Lakes on AWS S3
• Design Star Schema Data Models with Fact & Dimension Tables
• Implement Slowly Changing Dimensions (SCD1 & SCD2)
• Develop ETL Pipelines Using PySpark with Data Quality Checks
• Query and Explore Data Lakes with AWS Athena and Glue Catalog
• Automate Workflows and Pipelines Using Apache Airflow
• Create Custom Airflow Plugins to Manage EMR Spark Jobs
• Apply the WAP (Write-Audit-Publish) Pattern for Production Pipelines
• Implement Data Quality Frameworks and Data Contracts
• Deploy and Monitor Data Pipelines on AWS EMR
• Optimize Data Workflows for Cost, Performance, and Reliability
• Gain Hands-On Experience with Real-World Use Cases
• Prepare for Data Engineering Interviews with Confidence

Requirements

• Basic knowledge of SQL and Python
• Familiarity with Docker and Bash scripting helpful

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