Data Engineering Fundamentals

Course Overview

This foundational course introduces the role and responsibilities of a data engineer and maps out the complete data lifecycle, from generation to analysis, before tracing how data architectures have evolved — from traditional data warehouses, through data lakes, to the lakehouse and data mesh patterns used in modern platforms. It’s the bedrock course of the Data Engineer learning path: everything that follows, from Airflow orchestration to Dremio lakehouses, assumes the shared vocabulary and mental model built here.

The course closes on governance and security, treating them not as an afterthought but as core non-functional requirements of any data platform — particularly relevant in a sovereign cloud context where data residency and access control carry real regulatory weight. If you’re new to data engineering or coming from an adjacent role like software development or analytics, this is the course that establishes why the discipline exists and what a data engineer is actually responsible for day to day.

What You’ll Learn

• Describe the data engineer’s role and how it differs from adjacent roles like data science and analytics
• Map the end-to-end data lifecycle, from generation and ingestion to analysis
• Differentiate data warehouses, data lakes, data lakehouses, and the data mesh
• Apply core data governance, quality, and security principles in a sovereign cloud environment

Modules

• The Data Engineer Role and Responsibilities
• Data Lifecycle and Architectures
• Data Governance and Security

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