With a median gross salary of Rs 341.8 per hour, the IT sector in India has emerged as the most lucrative, followed by finance where employees get Rs 291 per hour, according to leading online career and recruitment solutions provider, Monster India.
Overall, the Monster Salary Index (MSI) shows that the median gross salary in the construction sector stood at Rs 259 per hour, for education at Rs 186.5, healthcare (Rs 215), legal (Rs 215.6), manufacturing and transport (Rs 230.9). The report brings to light the fact that employees in education sector get the lowest hourly salary of Rs 186.50 per hour.
This can be attributed to the fact that there are relatively more women working here than in other sectors and are paid 18 per cent lesser than men in the same sector, the report said.
Commenting on the findings of the report, Monster India Managing Director (India/Middle East/ Southeast Asia/Hong Kong) Sanjay Modi said: "The country is on the edge of a new wave of development that is expected to deliver jobs and prosperity to millions, which has a direct correlation with salary/income."
Across global and US region, the same survey indicates that females in the workplace are not being compensated in the same way as their male counterparts.
Meanwhile, gender pay gap is significant across sectors in India, it says. On average, women earn around 34 per cent less than men in the IT sector while gender pay gap in the finance sector is about 19 per cent.
"While we have seen a great increase in the number of women in supervisory positions, this does not reflect in the salary that those women are receiving," the report said.
"The MSI report is a standard systematic research and aimed at empowering recruiters and jobseekers with a credible platform to compare salaries," WageIndicator Foundation Director Paulien Osse said.
Monster Salary Index (MSI) is an initiative by Monster India in collaboration with Paycheck.in (managed by WageIndicator Foundation) and IIM-Ahmedabad as a research partner. The analysis is based on the WageIndicator dataset covering first quarter of 2012 up to December 2014.