What skills are required to be a Big Data Engineer?

An average Big Data Engineer in Canada makes CAD 101,605 in Canada, reveals Glassdoor. The report suggests that an entry-level Big Data Engineer earns CAD 112,500 yearly, while most experienced professionals make CAD 172,575 annually. The salary for Big Data Engineers varies dramatically depending on their experience and skills.

Do you want to become a Big Data Engineer and earn six figures per month but don’t know anything about data engineering and analytics? If yes, you must pursue a Data Engineering and Analytics course to polish your skills as a Big Data Engineer and turn yourself from a complete beginner to a professional.

To begin your career and develop the skills necessary to be a Big Data Engineer, you must understand their roles and responsibilities. It should be noted that a Big Data Engineer is an Information Technology professional who develops, builds, tests, and maintains complex data processing systems. The significant role of Big Data Engineers is to design the big data platform’s architecture and maintain a pipeline of data and structure data. They set up tools for data scientists to help them access data.

Now that you have a basic understanding of the roles and responsibilities of Big Data Engineers, this article will discuss the skills you require to become a competent Big Data Engineer.

Skills needed to become a Big Data Engineer

A Big Data Engineer requires expertise in various areas. The following are the top skills you will need to be a Big Data Engineer:

  1. Analytical skills

A Big Data Engineer needs to have hands-on experience observing, collecting, and using the information to analyze a problem. Big Data Engineers must be able to conduct and code Quantitative and Statistical Analysis. Therefore, a sound understanding of mathematics and logical thinking is crucial.

  1. Data visualization

Data visualization is another vital skill a Big Data Engineer requires to translate information into a visual context to make data more accessible for people to understand. In-depth knowledge of data visualization is imperative to identify patterns and trends in large sets of data.

  1. Database and SQL

In-depth knowledge of DBMS and SQL enables Big Data Engineers to manage and maintain data in a database. As a Big Data Engineer, you must know to write SQL queries for any Relational Database Management System. Some popular DBMS for Big Data engineering include MySQL and Oracle Database.

  1. Data mining

Gaining hands-on experience in data mining is essential to transform raw data into information necessary for business growth. Data mining enables the business to predict future trends and make informed decisions. Pictorial data mining, text mining, social media mining, and web mining are standard data mining types.

  1. Big Data tools

Knowledge of big data tools is essential for extracting data from various sources and transforming them into insightful information. Some commonly used Big Data tools are Apache Hadoop, Apache Spark, Flink, Apache Storm, MongoDB, SAS, and Tableau.

You can pursue a Data Engineering and Analytics course to gain all skills needed to kickstart your journey to becoming a Data Engineer. You can consider Canada to earn a degree in Data Engineering and Analytics for high-quality education and hands-on experience.

Show More

Related Articles

Leave a Reply

Your email address will not be published. Required fields are marked *

Check Also
Back to top button