Data Engineering is the foundation of the "big data" buzz.

If you are a well read professional, chances are you are well aware of the big data era. But still to provide a background, here is how I define the big data age :

  "With the recent advancement in the way we store,manage and process data, Companies can afford to get deeper insights in their data at the same or rather less cost than a decade ago."

With decent amount of experience in implementing big data projects from scratch, I can state with fair confidence that it is not very straight forward and is definately not a single player game. Big data is by far a team sport. A team that consists of Business Experts, Statisticians, Computer Scientist(also known as "Data Scientists") and Software Engineers(also termed as "Data Engineers"). 

The majority of the focus in terms of job growths are on Data Scientists and Data Engineers, and there is a good reason for that. If you look at the major changes that took place in past decade, you will soon notice that two particular fields have seen the most advancements viz Infrastructure and Data Mining, in that order.

Infrastructure is the foundation of the big data. With technologies like  Hadoop, Hive, HDFS, NoSql,etc. supported by Cloud Computing has enabled companies to store and leverage huge(and really huge) amount of data. This is the field that is also called as Data Engineering. Data Engineers are the workers who are in the basement of this gigantic ship. They hardly come to the top floors but are definately the ones making sure that the ship is not sinking.