Big Data Engineer

Writer : Angle Marque EG

There are many ways to get into the field of big data engineering.

It's no secret that Big Data Engineers are in high demand. This position is in high demand because it's a common term. Anyone interested in a career in Big Data should consider becoming a Big Data Engineer. As for how to get this position, have you ever wondered?

There's no need to look any further if you answered yes. In this blog, you'll learn everything you need to know about becoming a Big Data Engineer.

Introduction to Big Data

Learn the meaning of "Big Data" before diving into how to become a Big Data Engineer.

The amount of data that could be generated in the early years of the twenty-first century was relatively low. There has been a massive increase in the amount of data being generated thanks to the proliferation of social media platforms and multinational corporations around the world. In 2025, the IDC predicts that the total volume of global data will reach 175 zettabytes. Indeed, it's quite a lot of information to digest.

Datafloq and Statista have compiled the following statistics on Big Data and what the future holds:

Data is being generated at an unprecedented rate, both in terms of volume and speed. Having said that, the term "Big Data" encompasses a wide range of data types.

The following are various kinds of Big Data:

Data is being generated at an unprecedented rate, both in terms of volume and speed. Big Data, on the other hand, refers to a wide range of data formats.

With the help of these frameworks, Big Data Engineers are able to deal with all of this Big Data. Now that we've covered the basics, let's get into the nitty gritty of what it takes to become a Big Data Engineer.

Who is a Big Data Engineer?

As previously stated, the amount of data being generated around the world has increased significantly. The data, however, can only be useful if it is properly processed and analyzed. In order to get useful information from Big Data, it is analyzed. This results in better overall performance. Organizations can improve the quality of their business decisions, products, and marketing by following this advice. Professionals working in the area of Big Data also help.

The Big Data Engineer is one of the most sought-after positions in this industry. Those working in the field of Big Data Engineering are responsible for the design, implementation, testing, and evaluation of the company's Big Data systems. They have fun with Big Data and put it to good use for the company's advancement.

The responsibilities of both a Data Engineer and a Big Data Engineer can be performed by the same individual. Data engineers are now required to deal with Big Data as a result of the rise of the data management system. For this purpose, they learn Big Data engineering skills. There are numerous Big Data frameworks and NoSQL databases that a data engineer uses to manage Big Data.

There are a lot of different roles that a Big Data Engineer can play, so let's take a look at each one.

A Big Data Engineer's Job Description

Starting with the design of software systems, Big Data engineers collaborate and coordinate with data scientists. A Big Data Engineer's job responsibilities include the following:

  1. They are primarily in charge of conceptualizing, planning, and carrying out software projects. The systems are also checked and kept up to date by them.
  2. Systems for data ingestion and processing must be built by Big Data Engineers.
  3. Big Data Engineers perform the ETL process, which stands for Extract, Transform, and Load.
  4. Moreover, they are constantly looking for new ways to collect and improve the quality of their data.
  5. They also have to design data architectures that meet the needs of the company. By integrating various programming languages and tools, they are responsible for creating an organized solution.
  6. When it comes to building efficient business models, their primary responsibility is data mining from a variety of sources.
  7. Finally, Big Data Engineers collaborate with other teams, including data analysts and data scientists.

Big Data Engineers have a wide range of responsibilities, but these are just a few of them. A strong skill set is required to perform these duties.

After that, we'll take a closer look at Big Data Engineer skills.

Big Data Engineer Skills

A Big Data Engineer must have a wide range of knowledge and skills. The following are the most important Big Data Engineer skills:

  1. First and foremost, Big Data Engineers must be proficient programmers, as is true of many other high-tech occupations. Java, C++, or Python are among the most commonly used programming languages for Big Data Engineers.
  2. After programming, you'll need to know a lot about databases and SQL. This will help you understand how databases manage and maintain data. When working with any RDBMS, you'll need to know how to construct SQL queries. MySQL, Oracle Database, and Microsoft SQL Server are some of the most commonly used database management systems for Big Data engineering.
  3. One of the most important duties of a Big Data Engineer is to perform ETL operations, as was mentioned earlier. An understanding of data warehouse construction and use is required for this.

Engineers in the field of big data extract data from various sources, transform it into information, and then store it in various data storages. Talend, IBM Datastage, Pentaho, and Informatica are just a few examples of the software available for this task.

  1. Knowledge of operating systems is the fourth skill that you need. Big Data tools run on operating systems. As a result, a thorough knowledge of Unix, Linux, Windows, and Solaris is required.
  2. Tools and frameworks for Hadoop: You should be familiar with Hadoop-based analytical techniques. Hadoop is a common Big Data engineering tool, so familiarity with Apache Hadoop-based technologies like HDFS, MapReduce, Apache Pig, and Hive & HBase is a prerequisite.
  3. Having worked with real-time processing frameworks like Apache Spark is the sixth skill you need. A big data engineer needs an analytics engine like Spark that can be used for both batch and real-time processing, because you'll be dealing with massive amounts of data. When it comes to processing real-time streaming data from multiple sources, Spark is a great option.
  4. The final skill requirement is for you to have experience with data mining, data wrangling, and data modeling. It's important to note that data mining and data wrangling both include steps to preprocess and clean the data using various methods so that it's ready for analysis.

In order to gain new insights through data modeling, Big Data Engineers comb through enormous amounts of pre-existing data. Python, R, Rapid Miner, Weka, and KNIME are some of the tools used for this.

As you can see, becoming a Big Data Engineer necessitates a certain set of abilities. Let's take a closer look at the Big Data Engineer's career path next.

Are There Step-by-Step Instructions for a Big Data Engineer?

Organizations use Big Data to make critical decisions, creating an abundance of career opportunities.

Big Data Engineers in the United States can expect to earn anywhere from $66,000 to $130,000 per year. There is a wide range of salaries in India ranging from Rs.400,000 to Rs.14,000,000.

Besides Big Data Engineer, there are a few other roles in this field, including Data Architect, BI Architect, and Big Data Engineer.

Here's a visual representation of the path to becoming a Big Data Engineer:

As shown in the above roadmap, the first step is to earn a bachelor's degree and meet the requirements for Big Data Engineer skills. A Big Data certification course can also help you stand out from the crowd.

If you want to become a Big Data Engineer, you can get a few certifications that will help you along the way. Big Data Engineers can choose from the following certifications:

  1. CCP Data Engineer
  2. IBM Certified Data Architect – Big Data
  3. Google Cloud Certified Data Engineer
  4. Big Data Master's Program from Simplilearn

Simplilearn can help you in many ways, so what are some of them?

Simplilearn's Big Data Engineer Master's Certification program, developed in conjunction with IBM, is an excellent choice for anyone interested in a career in Big Data and Hadoop. The course consists of seven modules.

Big Data, Spark, PySpark, MongoDB, Cassandra, Scala, and other technologies are all available for study. Additionally, this course covers a wide range of essential tools, including Hadoop, Apache Spark, MongoDB, and Casandra.

What Do You Think of Big Data Engineering?

You've gained a basic understanding of Big Data after reading this article. There are many aspects of Big Data Engineers, including what a Big Data Engineer is, what they do, and how they do it. There was a path to becoming a Big Data engineer that you saw as well.

Simplilearn, on the other hand, can help you achieve your goal of becoming a Big Data engineer and kick-start your career. Upon completion of the Data Engineering Certification Training Program.

Have any questions about "How to Become a Big Data Engineer?" Please let us know. Please share your thoughts in the comments section below. We'll get back to you as soon as we can with one of our highly trained professionals!

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