Extract Transform Load Developer
647.500 kr. (DKK)/yr
311,30 kr. (DKK)/hr
22.404 kr. (DKK)/yr
The average extract transform load developer gross salary in Taastrup, Denmark is 647.500 kr. or an equivalent hourly rate of 311 kr.. This is 1% lower (-9.420 kr.) than the average extract transform load developer salary in Denmark. In addition, they earn an average bonus of 22.404 kr.. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Taastrup, Denmark. An entry level extract transform load developer (1-3 years of experience) earns an average salary of 460.698 kr.. On the other end, a senior level extract transform load developer (8+ years of experience) earns an average salary of 727.491 kr..
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704.086 kr. (DKK)
9 %
Based on our compensation data, the estimated salary potential for Extract Transform Load Developer will increase 9 % over 5 years.
This chart displays the highest level of education for:
Extract Transform Load Developer, 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 Taastrup, Denmark is 2% more than the average cost of living in Denmark. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageTaastrup (or Tåstrup) (Danish pronunciation: [ˈtsʰɒstʁɔp]) is a Danish railway town and suburb of Copenhagen – 18 km west of Copenhagen's city centre. The town forms a twin urban area with neighbouring suburb Høje Taastrup, Taastrup rising since 1859 and Høje Taastrup rising west of the town, since the 1970s. The town/suburb development has engulfed the villages of Taastrup Valby, Høje Taastrup, Kragehave and Klovtofte, although Høje Taastrup still has a preserved village character around Høje T
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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