Data Analytics Engineer
1 819 764 ₽ (RUB)/yr
874,89 ₽ (RUB)/hr
52 045 ₽ (RUB)/yr
The average data analytics engineer gross salary in Nizhny Novgorod, Russian Federation is 1 819 764 ₽ or an equivalent hourly rate of 875 ₽. This is 6% higher (+96 146 ₽) than the average data analytics engineer salary in Russian Federation. In addition, they earn an average bonus of 52 045 ₽. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Nizhny Novgorod, Russian Federation. An entry level data analytics engineer (1-3 years of experience) earns an average salary of 1 304 251 ₽. On the other end, a senior level data analytics engineer (8+ years of experience) earns an average salary of 2 277 293 ₽.
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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.
2 166 744 ₽ (RUB)
19 %
Based on our compensation data, the estimated salary potential for Data Analytics Engineer will increase 19 % over 5 years.
This chart displays the highest level of education for:
Data Analytics Engineer, the majority at 100% with bachelors.
Typical Field of Study: Data Modeling/Warehousing and Database Administration
See how education can impact your salaryThe 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.