What is the role of ETL in data engineering?

ETL (Extract, Transform, Load) is a core component of data engineering. It enables the movement of data from multiple systems—such as databases, APIs, and SaaS platforms—into centralized storage environments like data warehouses or data lakes. During transformation, data is cleaned, enriched, and reshaped for downstream analytics or machine learning.

A data engineering consultant uses ETL frameworks to automate and orchestrate this flow, ensuring scalability, accuracy, and compliance. Well-built ETL pipelines are foundational to modern data engineering solutions, supporting real-time decision-making and AI adoption.