If you have some of the new-age tech skills, not only are you likely to be hired much faster, you could also earn far better salaries. Terms like R, Julia, Hadoop, Scrum Master and Dev Ops may sound alien to most people, but these are some of the hot skills that companies are looking for. A youngster who has just started out and has learnt R, a popular programming language used for statistical computing to derive insights from data, gets an average salary of Rs 8 lakh a year, according to data from Simply learn, an online education provider of professional certification training. In comparison, the average salary for a regular fresher in an IT company is Rs 3.5 lakh. A mobile app developer or a Hadoop developer (Hadoop is a programming framework that supports the processing of large amounts of data in a widely distributed computing environment) can also get a similar salary. Age is not a factor here, it just depends on whether you have picked up the skills. These skills reflect the big shifts in the kind of software being used inside large firms today. This has been driven by the dramatic increase in mobile devices, the big jump in digital data, the need to analyze this data, and the phenomenon called cloud computing – use of remote servers hosted on the internet to store, manage, and process data, rather than a local server or a personal computer. Added to this is the emergence of what is called the internet-of-things – the trend to get everyday objects, be it a toaster, fridge, light fitting or an industrial machine, to communicate their status with remote computers or smartphones or even with one another. These are deep technology shifts changing the game for businesses. Five years ago, Java, C++ were sought-after skills, but IT companies are today looking at diversity in their tech talent pool to improve business conversation with their customers,” said Kashyap Dalal, chief product officer in Bengaluru-based Sachin Gupta, co-founder of online programming platform Hacker Earth, said R programming provides a very good way to quickly prototype and visualize data. “Its libraries in statistics and mathematics give a lot of power to data scientists to quickly manipulate data. Julia, which started as a scientific computing language, is gaining traction in the data sciences domain. Python, a programming language for data sciences, continues to be the language of choice after R because of its versatility,” he said.
