Data engineers rank amongst the topmost job roles across the globe.

Earning a lucrative job amid crucial times is incredibly challenging. Data is everywhere and undoubtedly data is termed as the new oil. Businesses are going digital with the potential to expand drastically. And over the past years, big data has been helping companies make better business decisions that have been accepted by the people. But if you don’t have the right talent to use big data and analytics, the company could go through a huge loss.

Today, a big data engineer and a data scientist are some of the most sought after job roles across the industry. From the finance to insurance sector, retail, and information technology, every industry has opened its doors for big data and analytics. Data engineers are professional who develops, constructs, tests, and maintains the architecture of a largescale processing system whereas big data engineers need to manage big data in the data management system. The role of data engineers has been upgraded. Now Big data engineers have to learn big data tools, frameworks, SQL databases to manage, design, and create the processing systems.

Based on multiple surveys and research, about 2.7 million data-related jobs will be available in the U.S. alone by the end of 2020. Picture this, with the ongoing COVID-19 pandemic, this number could exponentially grow bigger.

It is said by 2021, about 70 percent of the business leaders in the U.S. would prefer hiring professionals with data skills. Evidently, you will see that the number of professionals has started upskilling using the big data engineer program to make the most out of the jobs available in the market.

If you are seeking to acquire skills in big data, then consider learning the skillsets below.

Big data frameworks (Hadoop-based technologies) – there are a number of Hadoop-based tools that cater to different functions for different professionals. MapReduce, YARN, Pig, Hive, Flume, Sqoop, Oozie, Zookeeper, and Hadoop Distributed File System (HDFS) are some of the common technologies used for different purposes.

Python and R programming – most of the programming languages can serve the same purpose, therefore, in-depth knowledge in one of the programming languages will do the work. Though the flavor changes the logic remains the same. If you’re a beginner learning Python will be much easier because it is simple and has good community support. Whereas R is developed by statisticians and is majorly used by data analysts and data scientists in performing data analytics.

Real-time processing frameworks such as Apache Spark – real-time processing is crucial, be it a recommendation system or a credit card fraud detection system. As a data engineer, it is important to have a solid understanding of the real-time processing framework. Apache Spark can easily be integrated with Hadoop to leverage HDFS.

SQL-based technologies – the purpose of a Structured Query Language is to structure, manipulate, and manage the data stored in databases. Since data engineers work closely with relational databases, they need to have strong knowledge in SQL.

NoSQL technologies – for instance, MongoDB can store large volumes of structured or semi-structured data with agile structure as required. Some of the common NoSQL databases include technologies like Cassandra and HBase.

Data warehousing – data warehousing is critically important in terms of managing a large amount of data from heterogeneous sources where the ETL (Extract, Transform, and Load) is used. This majorly used for data reporting and data analytics, which is an important part of business intelligence.

MS Windows, UNIX, and Linux – these are some of the most prominent operating systems used in the industry. As a big data engineer, the individual needs to be proficient with at least one of them.

Data keeps generating and it is changing the way businesses function. As companies grow, so will the need for data professionals. Managing data has become essential for almost all industries. Thus, becoming a big data professional is an ideal career choice you’ll be making today.

The demand for data professionals is huge, even big giants such as Microsoft, IBM, JP Morgan Chase, Apple, Google, Amazon, Accenture, and Boeing are seeking talents with big data skills. Not to mention, since the job roles are in-demand companies are even willing to pay the talents lucrative compensation.

So, what are you waiting for? Begin your career in big data and be a part of the desired talent pool.