Building Information Modeling Coordinator
1 848 313 ₽ (RUB)/yr
888,61 ₽ (RUB)/hr
51 938 ₽ (RUB)/yr
The average building information modeling coordinator gross salary in Nizhny Novgorod, Russian Federation is 1 848 313 ₽ or an equivalent hourly rate of 889 ₽. This is 7% higher (+113 873 ₽) than the average building information modeling coordinator salary in Russian Federation. In addition, they earn an average bonus of 51 938 ₽. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Nizhny Novgorod, Russian Federation. An entry level building information modeling coordinator (1-3 years of experience) earns an average salary of 1 313 308 ₽. On the other end, a senior level building information modeling coordinator (8+ years of experience) earns an average salary of 2 318 721 ₽.
This page is a promotion for SalaryExpert’s Assessor Platform and is not intended for professional use.
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ERI’s compensation data are based on salary surveys conducted and researched by ERI. Cost of labor data in the Assessor Series are based on actual housing sales data from commercially available sources, plus rental rates, gasoline prices, consumables, medical care premium costs, property taxes, effective income tax rates, etc.
2 200 736 ₽ (RUB)
19 %
Based on our compensation data, the estimated salary potential for Building Information Modeling Coordinator will increase 19 % over 5 years.
Education data not available for this job
The cost of living in Nizhny Novgorod, Russian Federation is 7% less than the average cost of living in Russian Federation. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
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This page is a promotion for SalaryExpert’s Assessor Platform and is not intended for professional use.
Professionals should subscribe to SalaryExpert’s Assessor Platform.
ERI’s compensation data are based on salary surveys conducted and researched by ERI. Cost of labor data in the Assessor Series are based on actual housing sales data from commercially available sources, plus rental rates, gasoline prices, consumables, medical care premium costs, property taxes, effective income tax rates, etc.