Background Job burnout and depressive symptoms are prevalent among occupational populations, with a close relationship between them. Sleep quality, as a potential mediating factor, significantly affects the mental health of workers. Objective To explore the relationship between job burnout, sleep quality, and depressive symptoms, and determine whether sleep quality mediates the relationship between job burnout and depressive symptoms. Methods From April 25 to May 1, 2024, this study employed cluster sampling to conduct a questionnaire survey among individuals engaged in various occupations across five cities in the Ningxia Hui Autonomous Region. The questionnaires included socio-demographic information, as well as the Chinese Maslach Burnout Inventory (CMBI), the Pittsburgh Sleep Quality Index (PSQI), and the Patient Health Questionnaire-9 (PHQ-9) for assessing burnout, sleep quality, and depressive symptoms, respectively. Out of the 4106 questionnaires distributed, a total of 3837 questionnaires were valid, and the valid recovery rate was 93.45%. The distribution among demographic variables in burnout, sleep quality and depressive symptoms were statistically analyzed. A binary logistic regression model was used for multifactor correlation analysis; Pearson correlation was used to test the correlation between burnout, sleep quality, and depressed mood. Modelling and mediated effect path mapping were performed using Amos 24.0 software. Results The postive rate of occupational burnout in the workers was 97.49% (3741/3837), the positive rate of poor sleep quality was 66.77% (2526/3837), and the positive rate of depressive symptoms was 75.68% (2904/3837). There were statistically significant differences in depressive symptoms by ages, shift types, working years, marital status, smoking habits, drinking habits, and exercising frequency (P < 0.05). The logistic model indicated that working years, drinking habits, job burnout, and overall sleep quality were significant factors influencing the occurrence of depressive symptoms (P < 0.05). The correlation analysis revealed positive correlations between depressive symptom scores and job burnout scores (r=0.045, P < 0.01), between depressive symptom scores and sleep quality scores (r=0.480, P < 0.01), and between job burnout scores and sleep quality scores (r=0.054, P < 0.01). Furthermore, the indirect effect of job burnout on depressive symptoms through sleep quality was 0.100 (95%CI: 0.204, 0.252; P < 0.01). Conclusion Job burnout and sleep quality are significant factors associated with the occurrence of depressive symptoms among occupational populations, and sleep quality plays a partial mediating role in depressive symptoms associated with job burnout. This finding may provide a scientific basis for developing intervention strategies to control depressive symptoms among workers.