How to Become Big Data Engineer?

Introduction

Before learning about - How to become Big Data Engineer? Let us learn about Big data first. Big data is an ever-growing large set of data. These huge collections of data are growing exponentially with time.

We generate tons of data daily, and normal tools and technologies cannot process them easily. We use special tools and technologies like Apache Hadoop, HPCC, Storm, Zoho Analytics, etc. Since data is so important these days, apart from specialized tools, we need a dedicated team of engineers to deal with it. So, the person who works around Big Data is known as a Big data engineer. Let us now learn about this profession in detail in the next sections.

What does a Big Data Engineer Do?

As discussed in the Introduction section, Data is the most important thing today. Now, the engineers interacting with such massive data sets are known as Big Data Engineers. Big data engineers deal with real-time data processing, large-scale data present in the databases, etc. Big data engineers are an important part of any organization as they help the organization deal with massive sets of data and then utilize analysis for the further benefit of the company. Let us take an example to understand the work and importance of Big data engineers in any organization.

Let us take the example of Amazon's shopping website. Millions of users visit the Amazon website and generate tons of data daily. Suppose you have opened Amazon and searched for shirts. Now Amazon would ask you to save your data in their database so that whenever you visit the website again, Amazon can show you recommendations based on your preference and previous searches.

Now whenever you open the Amazon website again, it will show shirts according to your preferences, size, color, pattern, price range, brand, etc. So now the question arises: How does Amazon collect, manage, and use this data to showcase products of our preferences? Several dedicated teams of Big Data engineers help Amazon showcase our preferences.

Task Responsibility

Let us now discuss the various tasks and responsibilities of Big Data engineers. The most important task of a Big data engineer is to process and analyze the collected data to predict valuable and actionable insights.

Big Data engineers perform tasks like,

• Data processing
• Data filtering
• Data classification
• Data analysis
• Identify market demographics
• Predict upcoming changes and trends

Some of the major responsibilities of a Big data engineer are:

• Process and analyze large sets of data to get valuable insights.
• Develop and Design algorithms for predictive models.
• Build scalable data management systems.
• Ensure the proper functioning of data analytics tools and data systems.
• Research the collected data to improve the quality and efficiency of data.
• Design and Develop custom software and apps for analysis work.
• Develop data set to train predictive models, etc.

Big Data engineers utilize the collected data to benefit the organization in healthcare, science, advertisement, social media, finance, telecommunications, and other industries.

Why Become a Big Data Engineer?

After learning about How to become Big Data Engineer, Let us learn why we should opt for this profile.

• High demand:
  As more and more businesses see the potential of data-driven decision-making, demand for big data engineers is rising quickly. Due to the increasing demand for qualified individuals in this industry, there may be prospects for job security and professional advancement.
• Fascinating work:
  Big Data Engineers get to work with cutting-edge technologies and large data sets. As you will be responsible for planning and building data pipelines, evaluating data, and implementing data storage and processing solutions, this can be intellectually stimulating and satisfying work.
• Competitive salaries:
  Big Data Engineers are often well-compensated due to their specific talents and the great demand for expertise. Wages can range from roughly $90,000 to more than $175,000 per year, based on experience, geography, and other considerations.
• Possibilities for promotion:
  There are several prospects for advancement and growth as a Big Data Engineer. You could advance to the Senior Big Data Engineer or Lead Big Data Engineer position or move into similar roles such as Data Scientist or Machine Learning Engineer by further upskilling yourself with relevant courses.
• Making a difference:
  Big Data Engineers can greatly impact their firm's performance by working with data and assisting enterprises in making better decisions. This can be rewarding employment because you will assist in achieving real-world results and constructive change.

Becoming a Big Data Engineer might be a fantastic decision for those who enjoy working with data, are interested in technology, and seek a satisfying and challenging profession with significant growth potential.

What is the Typical Background of a Big Data Engineer?

A big data engineer designs develop and manage the infrastructure for processing and analyzing huge, complicated data sets. This entails creating data pipelines, putting data processing and storage systems into place, and assuring data security and accessibility.

A Big Data engineer turns the messy collected data into accurate, clean, and actionable data so that the data analysis can be performed easily and data reports can be made easily.

To become a successful Big data engineer, one should have good problem-solving ability and data integration knowledge.

Big Data Engineer Roadmap: How to Become a Big Data Engineer?

Let us now discuss our topic i.e. How to become Big Data Engineer in a step-by-step manner.

1. Education

To become a Big Data engineer, you should have a deep interest in mathematics, computer science, statistics, computer engineering, etc. To become a Big data engineer, one should have a Bachelor's degree in computer science-related fields.

Let us now discuss some of the technical areas in which a Big Data engineer should be proficient:

• Databases including SQL and NoSQL, such as
  • PostgreSQL
  • MySQL
  • MongoDB
  • Cassandra, etc.
• Hadoop ecosystem (Hive, Pig, HBase, MapReduce, etc).
• Operating systems such as UNIX, Linux, Solaris, etc.
• Programming Languages such as R, Python, Scala, Java, etc.
• Statistics and analysis.
• Libraries and frameworks like MatLab, NumPy, Pandas, SAS, etc.
• Business Analytics tools like Microsoft Power BI, Microsoft Azure, etc.
• Spark ecosystem and Streaming tools.

In the field of Big Data, Python is often the choice of Big Data Engineers because of its easy and friendly commands, cumulative and fast modules, etc. Moreover, Data Scientists prefer Python for Data Analysis as these analyzed data can be easily integrated with web applications and other production environments. Furthermore, the wide variety of uncountable and highly optimized libraries like Pandas, NumPy, BeautifulSoup, OpenCV, etc., and the easy syntax make Python one of the favourite programming languages in Big data analysis, so one should learn Python as well.

2. Work Experience

As discussed, we need analytical, problem-solving, and database integration knowledge. Therefore, if a Big Data engineer is working and wants to advance in this field, they should continue learning and learn some advanced tools and technologies like Airflow, Delta Lake, Apache Drill, Apache Flink, Hadoop, HPCC Systems, Hive, Pig, etc.

3. Certification

One can also go for some professional certifications to showcase themselves among competitors. Some of the certifications related to the field of Big Data are:

• Google Cloud Certified Professional Data Engineer.
• Cloudera Certified Professional (CCP) Data Engineer.
• Certified Big Data Professional (CBDP).

Big Data Engineer Salaries

As we have earlier discussed the importance of Big Data engineers in organizations, Big Data engineers are in high demand as data is crucial in almost every field. As a result, Big Data engineering is one of the highest-paying jobs in IT.

Let us now discuss some of the Big Data engineer roles and their respective salaries.

According to BLS (Bureau of Labor Statistics), a Big data engineer's salary may range between $66,000 to $130,000. The annual salary of a Big data engineer is around $90,000.

According to Glassdoor research, an American Big Data Engineer pays an average of about $125,000 annually. Yet, depending on the area and business, earnings might vary from $90,000 to $175,000.

These salaries largely depend upon the type of company, role, education, experience, and job location. For example, the salary tends to increase more according to the education and experience level of the Big data engineer.

Employment Outlook for Big Data Engineers

According to the BLS, the employment forecast for Big Data Engineers coming under the category of computer programmers, information research scientists, and statisticians is optimistic due to increased demand for data-driven decision-making, quickly expanding technology, globalization of enterprises, and emerging sectors like AI and ML. Therefore, it is a great career choice for people interested in technology, data analysis, and generating tangible outcomes because there is considerable demand for it, and high growth is expected shortly.

According to BLS, this profession will grow by 34% between $2020- 2026$, which is quite fast. Moreover, according to research, it is the seventh fastest-growing field in IT.

Our Course

You can also join our course to get an in-depth understanding of Big Data, how it works, and how you can master this technology. Check out Scaler's Data Science Courses to get started.

Additional Resources

1. Application of Big Data