Starting out in the world of big data can be daunting, but it’s worth it. So if you’re interested in this growing field and want to learn more about how to make the leap from where you are today to your end goal, look no further than Udemy. Here are the top things that you need to know if you want to become a big data engineer.
how to become a big data engineer
With the era of big data and cloud computing, there has been a significant increase in data analysis jobs. A big data engineer is responsible for the implementation of a company’s data-processing strategy. This can include managing various data types and determining the best way to store massive volumes of data that need to be processed quickly.
What Is Big Data Engineering?
You’ve probably heard of the concept of big data—the troves of user information and recorded actions generated by social media platforms such as Facebook, Twitter, and TikTok, ecommerce stores like Amazon, and a whole range of websites and services ranging from The New York Times to cloud storage hosts. Big data is so overwhelming in breadth and quantity that it is impossible for humans to parse through in its raw form to glean insights. This is where big data engineering enters the picture.
Big data engineering focuses on the infrastructure that allows people to collect and organize all that data—the millions to billions of clicks, taps, likes, swipes, shares, and purchases—in a way that is usable. They do this through building data pipelines, designing and managing data infrastructures such as big data frameworks and databases, handling data storage, and focusing on the ETL (Extract, Transform, Load) process.
What Does a Big Data Engineer Do?
If big data engineering is about the infrastructure used to process data, it helps to think of big data engineers as data architects responsible for building, maintaining, and improving that infrastructure. To do this, big data engineers need an in-depth knowledge of SQL and NoSQL databases, as well as database solutions such as Cassandra, Bigtable, and Hadoop.
With these skills, big data engineers build and maintain data workflows, which enable other data professionals such as data scientists and data analysts to hypothesize, test, and analyze the collected data. In other words, data engineers make it possible for big data to become usable.
About the Role of Big Data Engineer
Big data engineers, also commonly referred to as data engineers, are the software programmers of the field of big data. While the job description of a data engineer might slightly differ from organization to organization, the skills and responsibilities required tend to be similar across the board.
Big Data Engineer Job Description
Data engineers are responsible for transforming large amounts of data into formats that can be processed and analyzed. This requires significant technical skill, including knowledge of multiple programming languages and SQL and AWS technologies. While the skill level required varies from junior data engineering roles to more senior roles, the job description will usually contain clues as to what a candidate needs to know in order to qualify, such as the types of programming languages a data engineer needs to know, the company’s preferred data storage solutions, and context on the teams the data engineer will work with.
Big Data engineers are in huge demand. The problem I find, teams don’t know where to start. Not only are there several skills that need to be learned, but organisations need to appreciate the talent required to build the solutions. A systems programmer, an administrator, a data analyst, a designer and maybe even a statistician!
