Information Processing Engineer
44 665 € (EUR)/yr
21,47 € (EUR)/hr
1 925 € (EUR)/yr
The average information processing engineer gross salary in Vilnius, Lithuania is 44 665 € or an equivalent hourly rate of 21 €. This is 13% higher (+4 989 €) than the average information processing engineer salary in Lithuania. In addition, they earn an average bonus of 1 925 €. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Vilnius, Lithuania. An entry level information processing engineer (1-3 years of experience) earns an average salary of 31 417 €. On the other end, a senior level information processing engineer (8+ years of experience) earns an average salary of 51 157 €.
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58 276 € (EUR)
30 %
Based on our compensation data, the estimated salary potential for Information Processing Engineer will increase 30 % 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 Vilnius, Lithuania is equal to the average cost of living in Lithuania. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageVilnius ( VIL-nee-əs, Lithuanian: [ˈvʲɪlʲnʲʊs] ) is the capital of and largest city in Lithuania and the most-populous city in the Baltic states. The city's estimated January 2026 population was 617,984, and the Vilnius urban area (which extends beyond the city limits) has an estimated population of 747,864. Vilnius is notable for the architecture of its Old Town, considered one of Europe's largest and best-preserved old towns. The city was declared a UNESCO World Heritage Site in 1994. The arc
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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