Occupational stress is a complex process affecting health and performance. Air Traffic Control is a complex and demanding profession. The current study demonstrates the concept of using a biomonitoring wearable platform (BWP), that combines self-report measures with biomarkers, to track stress among Air Traffic Controllers. A wearable ECG device was used to gather continuously medical-grade ECG data along with a mobile app for daily stress perception, symptoms and events annotation. A total of 256 hours of data from 32 routine work shifts and 5 days-off, from 5 ATCs was recorded with 35 tagged events using Heart Rate Variability metrics- AVNN, RMSSD, pNN50 and LF/HF were computed from ECG data and analyzed during a) shifts vs days off; b) events vs non-events and c) before and after working pauses. ATCs showed low levels of chronic stress using self-reports. Results showed that stress symptomatology slightly increase from the beginning to the end of the shift (Md=1 to Md=2; p<0.05). Statistical significant physiological changes were found between shifts and days off for AVNN and LF/HF (p<0.05), showing higher physiological activation during shifts. A significant reduction of physiological arousal was verified after working pauses, particularly for AVNN and LF/HF (p<0.001). Self-reported data also suggests the same trend (p<0.005). Findings reinforced the discriminatory power of AVNN and LF/HF for short-term stress classification using HRV measurements. Results suggest that the rotating working system, with pause/resting periods included, effective acted as a recovery period.Clinical Relevance-Results provide important clues to the impact of stress on health, particularly cardiac reactivity and the identification of stress quantitative biomarkers as diagnostic indicators, providing a more reliable source for stress monitoring than currently behavioral or subjective measures. Findings will help on the design of stress management programs and prevention actions in order to avoid the negative effects of stress.