Digital recruitment platforms are increasingly used in academic environments to manage doctoral applications and hiring processes. While existing systems primarily focus on applicant-facing workflows, administrative coordination and data protection requirements often remain insufficiently supported. This thesis addresses these gaps by extending the TUM Doctoral Application Portal (TUMApply) with structured administrative management and GDPR compliant data governance mechanisms. The work introduces an approval-based research group management workflow that enables administrators to manage academic entities such as schools, departments, and research groups, while allowing professors to maintain their research groups in a controlled and auditable manner. A refined role model is implemented to distinguish between applicants, professors, employees, and administrators, supporting decentralized yet transparent administration. In addition, data protection requirements are operationalized through user-accessible data export functionality, automated data retention, and deletion processes aligned with Articles 17 and 20 of the GDPR. The system design follows a modular client–server architecture, integrating the new features into the existing TUMApply platform without disrupting established recruitment workflows. By embedding administrative governance and privacy-by-design principles directly into the system architecture, this thesis contributes to the development of scalable, secure, and institutionally governed academic recruitment platforms.