Engineer Data Virtualization
Rs 3,128,314 (PKR)/yr
Rs 1,504.00 (PKR)/hr
Rs 135,143 (PKR)/yr
The average engineer data virtualization gross salary in Rawalpindi, Pakistan is Rs 3,128,314 or an equivalent hourly rate of Rs 1,504. This is 5% higher (+Rs 155,748) than the average engineer data virtualization salary in Pakistan. In addition, they earn an average bonus of Rs 135,143. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Rawalpindi, Pakistan. An entry level engineer data virtualization (1-3 years of experience) earns an average salary of Rs 2,234,971. On the other end, a senior level engineer data virtualization (8+ years of experience) earns an average salary of Rs 3,625,784.
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Rs 4,634,630 (PKR)
48 %
Based on our compensation data, the estimated salary potential for Engineer Data Virtualization will increase 48 % over 5 years.
This chart displays the highest level of education for:
Engineer Data Virtualization, 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 Rawalpindi, Pakistan is 7% less than the average cost of living in Pakistan. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageRawalpindi, colloquially known as Pindi, is the third-largest city in the Pakistani province of Punjab, serving as the principal commercial and industrial hub of northern Punjab. It is the fourth-most populous city in Pakistan and ranks as the world's third-largest Punjabi-speaking metropolis (after Lahore and Faisalabad). Located along the Soan River in north-western Punjab, Rawalpindi lies adjacent to Pakistan's capital, Islamabad, and the two are jointly known as the "twin cities". Located on
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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