Big Data Developer
kr 933 635 (NOK)/yr
kr 448,86 (NOK)/hr
kr 37 999 (NOK)/yr
The average big data developer gross salary in Fredrikstad, Norway is kr 933 635 or an equivalent hourly rate of kr 449. This is 5% lower (-kr 51 963) than the average big data developer salary in Norway. In addition, they earn an average bonus of kr 37 999. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Fredrikstad, Norway. An entry level big data developer (1-3 years of experience) earns an average salary of kr 657 266. On the other end, a senior level big data developer (8+ years of experience) earns an average salary of kr 1 055 988.
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kr 1 066 761 (NOK)
14 %
Based on our compensation data, the estimated salary potential for Big Data Developer will increase 14 % over 5 years.
This chart displays the highest level of education for:
Big Data Developer, the majority at 100% with bachelors.
Typical Field of Study: Computer Programming, Specific Applications
See how education can impact your salary- Pega Certified Data Scientist (PCDS)
The cost of living in Fredrikstad, Norway is 5% less than the average cost of living in Norway. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageFredrikstad (Norwegian: [ˈfrɛ̀drɪkstɑ] ; previously Frederiksstad; literally "Fredrik's Town") is a port city and municipality in Østfold county, Norway. The administrative centre of the municipality is the city of Fredrikstad. The city of Fredrikstad was founded in 1567 by King Frederick II, and established as a municipality on 1 January 1838 (see formannskapsdistrikt). The rural municipality of Glemmen was merged with Fredrikstad on 1 January 1964. The rural municipalities of Borge, Onsøy, Krå
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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