Virtualization Engineer - Data
919.053 kr (SEK)/yr
441,85 kr (SEK)/hr
39.703 kr (SEK)/yr
The average virtualization engineer - data gross salary in Skelleftea, Sweden is 919.053 kr or an equivalent hourly rate of 442 kr. This is 2% lower (-18.770 kr) than the average virtualization engineer - data salary in Sweden. In addition, they earn an average bonus of 39.703 kr. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Skelleftea, Sweden. An entry level virtualization engineer - data (1-3 years of experience) earns an average salary of 645.693 kr. On the other end, a senior level virtualization engineer - data (8+ years of experience) earns an average salary of 1.038.620 kr.
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1.029.042 kr (SEK)
12 %
Based on our compensation data, the estimated salary potential for Virtualization Engineer - Data will increase 12 % over 5 years.
This chart displays the highest level of education for:
Virtualization Engineer - Data, the majority at 100% with bachelors.
Typical Field of Study: Computer Programming, Specific Applications
See how education can impact your salaryThe cost of living in Skelleftea, Sweden is 0% less than the average cost of living in Sweden. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageSkellefteå (Swedish: [ɧɛˈlɛ̌ftɛɔ], locally [ʂɛˈlɛ̌ftɛ] ; Meänkieli: Heletti) is a city in Västerbotten County, Sweden, with a population of 36,388. It is the seat of Skellefteå Municipality, which had 77,322 inhabitants in 2024. The city is historically industrial, with mining being a large part of that industry, especially for gold, leading to the city being nicknamed Guldstaden ("gold town"). Politically, Skellefteå is a Social Democratic stronghold. The city is a well-known ice hockey town, w
Sourced from WikipediaERI'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.
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