Structured Query Language Analyst
697.718 kr. (DKK)/yr
335,44 kr. (DKK)/hr
22.676 kr. (DKK)/yr
The average structured query language analyst gross salary in Arhus, Denmark is 697.718 kr. or an equivalent hourly rate of 335 kr.. This is 8% lower (-57.137 kr.) than the average structured query language analyst salary in Denmark. In addition, they earn an average bonus of 22.676 kr.. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Arhus, Denmark. An entry level structured query language analyst (1-3 years of experience) earns an average salary of 490.045 kr.. On the other end, a senior level structured query language analyst (8+ years of experience) earns an average salary of 787.813 kr..
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759.440 kr. (DKK)
9 %
Based on our compensation data, the estimated salary potential for Structured Query Language Analyst will increase 9 % over 5 years.
This chart displays the highest level of education for:
Structured Query Language Analyst, 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 Arhus, Denmark is 1% less 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 PageAarhus (, US also ; Danish: [ˈɒːˌhuˀs] , locally also [ˈɒːˌhus]) is the second-largest city in Denmark and the seat of Aarhus Municipality. It is located on the eastern shore of Jutland in the Kattegat sea and approximately 187 kilometres (116 mi) northwest of Copenhagen. Its urban population was 301,049 in 2025. Dating back to the late 8th century, Aarhus was founded as a harbour settlement at the mouth of the Aarhus River and quickly became a trade hub. The first Christian church was built the
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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