The article focuses on the principles and practices of security data engineering and ETL (Extract, Transform, Load) processes, emphasizing the importance of data protection and compliance in the handling of sensitive information. It discusses various strategies for implementing secure ETL workflows while ensuring data integrity and accessibility. Best practices and tools are also highlighted to aid professionals in improving their data engineering processes.

Data engineers play a crucial role in achieving GDPR compliance by implementing systems that manage personal data responsibly. This guide outlines key concepts such as encryption, hashing, and anonymization, as well as best practices for designing data architectures that ensure privacy and security. It also covers practical considerations for incident response and interview preparation related to GDPR.