In a really short period of time, it seems like the field of big data analytics has frog leap to its current status of the most lucrative career option. Within itself as well, there are quite a number of interesting options for those looking for an adventurous yet exciting career ride in their future.
Of these options one can opt for positions like a Data Scientist, A Data Engineer, A Big Data Engineer (yes, the two differ from each other), Machine Learning Scientist, Business Analytics Specialist, Data Visualization Developer, Business Intelligence Engineer, BI Solution Architect, BI Specialist, Analytics Manager, Machine Learning Engineer, Statistician and so on.
Also Read: Salary Trends in Big Data Industry
Professionals who usually work at these high profile positions, tend to generally rake in impressive salary packages. Someone who works as a Big Data Engineer generally tends to earn comparatively more than their counterparts who are in involved in jobs such as data management and administration. In terms of job responsibilities, this professional has to oversee the various analytical programs that are used by their company. At the same time, they have to closely work with data architects, various analysts and other professionals in order to obtain valuable insights.
Someone who works as a Data Architect often earns quite equal to the Big Data Engineers. These professionals need to have a mixture of both business and technical skills as they are required to fully understand what kind of information is required by business leaders from the data that they seem to have collected and then go on to both design and deploy their databases, data warehouses and data lakes and so on. A bachelor’s degree is the least minimum requirement needed for getting into this field, having some knowledge about how the software works beforehand is one other benefit for the job.
The position of a Data Scientist is time and again touted as one of the ‘sexiest’ positions by many of the various companies as well as magazines and publications out there. While the demand for data scientists was skyrocketing when this career was introduced for the first time, today it seems to have waned off a little. But at the same time, the salaries have consistently remained very high. Data Scientists are popularly known as the masters of statistics. They are supposed to not just get data, but they are also supposed to clean it, transform it, build data models, apply algorithms and as well as create visualizations that help the business leaders get the perfect kind of insights from them.
One very common prerequisite for all of these job descriptions is just that you need to learn programming languages. These languages could range from R Programming, SAS Programming, Big Data Hadoop, SQL, Python, Pig and so on. While some of these can be learned on your own but then again there are some which need to be taught under proper guidance. This is why the majority of candidates opt for professional training classes which prepare them for the industry, like the ones offered by Imarticus Learning.
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