Human resource management, by emphasizing human capital as a central organizational asset, plays an important role in organizational performance and competitive advantage. Employee onboarding supports the structured entry and adaptation of new employees to organizational roles, expectations, and work practices. This single case study applies process mining to analyze and redesign an employee onboarding process using real event log data from an Iranian company in the online tourism services sector. The study examines 293 completed or progressing onboarding cases recorded over twenty months. Celonis and three process discovery algorithms, Inductive Miner, Heuristic Miner, and Alpha Miner, were used within the ProM framework to examine process behavior and model quality. Among the three evaluated algorithms, Inductive Miner provided the most suitable model for this event log under the selected evaluation criteria, although its Fitness and Precision values indicate important limitations. The analysis identified long duration activities, repeated work, unnecessary dependencies, and control related interruptions as priority areas for review. Based on the proposed redesign and the stated calculation assumptions, selected activity removals and consolidations were associated with estimated reductions in process time and scenario based cost. These estimates are model based and should not be interpreted as independently verified post implementation outcomes. The study contributes an applied case based analysis that links process discovery, bottleneck diagnosis, stakeholder informed redesign, and operational evaluation within an employee onboarding setting, while recognizing that the specific results remain dependent on the case context and the available event data.