Information Processing Engineer
831.921 kr. (DKK)/yr
399,96 kr. (DKK)/hr
35.856 kr. (DKK)/yr
The average information processing engineer gross salary in Køge, Denmark is 831.921 kr. or an equivalent hourly rate of 400 kr.. This is 3% lower (-29.200 kr.) than the average information processing engineer salary in Denmark. In addition, they earn an average bonus of 35.856 kr.. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Køge, Denmark. An entry level information processing engineer (1-3 years of experience) earns an average salary of 581.767 kr.. On the other end, a senior level information processing engineer (8+ years of experience) earns an average salary of 943.115 kr..
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904.625 kr. (DKK)
9 %
Based on our compensation data, the estimated salary potential for Information Processing Engineer will increase 9 % over 5 years.
This chart displays the highest level of education for:
Information Processing Engineer, the majority at 54% with bachelors.
Typical Field of Study: Computer Support Specialist Training
See how education can impact your salaryThe cost of living in Køge, Denmark is 5% 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 PageKøge (Danish pronunciation: [ˈkʰøː(j)ə], older spelling Kjøge) is a Danish seaport on the coast of Køge Bugt (Bay of Køge) 39 km southwest of Copenhagen. It is the principal town and seat of Køge Municipality, Region Zealand, Denmark. In 2025, the urban area had a population of 38,506. The natural harbour and strategic location have given Køge a long history as a market town. Today, that past is evident in a well-preserved old town centre with many half-timbered houses. Køge is located in the Co
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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