While the entire Information Technology Industry is soaked fears relating to layoffs, the number of job opportunities in Big Data Analytics has nearly doubled in 2017. In our previous article, we discussed about the ‘Soaring Demand for Analytics Professionals’. Between April 2016 and April 2017, the number of analytics jobs almost doubled.

Big Data engineering is a new field with a lot of new technologies and new positions. Not all roles require expertise in every area, so pay attention to what needs the company you’re looking at really has. By taking on one of these roles, you’re tackling a brand new field with lots of possibilities, which means you need to be flexible and open to learning on the fly to do the most amazing work possible. Not all Big Data roles are the same, but there are a few things you can expect to see if you take on a position in this field. Typically the role will include a subset of the following high-level skills:

Skill #1: Collection of Data

Data collection is the process of gathering and measuring information on targeted variables in an established systematic fashion, which then enables one to answer relevant questions and evaluate outcomes. As a Big Data Engineer, you will have to extract data from programming interfaces, websites, etc. to gather information. You must be skillful in collecting and creating data models for information systems by applying SQL expertise and certain other techniques.
Skill #2: Transformation of Data

In computing, data transformation is the process of converting data from one format or structure into another format or structure. Informatica, DataStage, SSIS and Redpoint are some of the most popular ETL (Extract, transform, load) tools used in Transformation of Data.
Skill #3: Storing the Data (Data Warehousing)

Data Warehouses are used to store current and historical data in one single place that are used for creating analytical reports for knowledge workers throughout the enterprise. MySQL, MS SQL Server and Oracle are some of the most popular tools used to store Big Data. It takes lot of time to master these tools, but learning them is of great worth. In the recent times, Data storage software experts are in big demand.
Skill #4: Analysis of Data (Data Analytics)

Data analysis, also known as analysis of data or data analytics, is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. In Data Analysis you should be specialized in certain tools like MapReduce, Hadoop, Cloudera, MapR, etc. It will be of great advantage if you can master Statistical analysis software like R, SPSS, SAS and MATLAB. Moreover, recruiters also look for programming skills; learn Java, Ruby or C++ to prove you are fit to become a competent Big Data Engineer.