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Data Engineering: Profession, Skills, Career Path

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The vast amount of data is changing the principles of doing business and also creating a demand for data engineers who can collect, store, and sort it. It’s expected that by 2025 we will produce 463 exabytes of data daily. Processing information of this scale will be impossible without industry specialists. Therefore, data engineering will become an important part of future global changes.

 

If you work in programming and want to be part of a challenging process, read the blog and find out what opportunities data engineering offers.

What does data engineering involve?

 

Data engineers work on designing and creating systems that collect, process, and transform primary data into usable information for data scientists and business analysts. Their main goal is to make data accessible in such a way that the organization can use it to evaluate and optimize business.

This is an incomplete list of responsibilities you might have when working with data:

  • Collecting databases that relate to business needs
  • Developing algorithms that transform data into practical information
  • Building, testing, and maintaining the system architecture of databases
  • Collaborating with managers to understand company goals
  • Creating new methods and tools for data validation and analysis
  • Ensuring compliance with data management and security policies

Why should you choose data engineering?

Working in this field is both enjoyable and challenging. You will play an important role in the company’s success. You achieve this by making data easily accessible to data scientists, analysts, and decision-makers. They need this information in their daily activities. For this, you will need programming and problem-solving skills.

 

As long as data exists, there will be a demand for data engineers. Moreover, according to a 2019 study, data engineering is the trendiest job in the technology industry. It leaves behind computer scientists, web designers, and database architects

 

In addition, data engineering is a high-paying profession – according to 2022 statistics, the average income in the US is $115,176.

To become a successful data engineer, it’s desirable to have relevant knowledge and skills in computer science. This will create the foundation needed in this rapidly developing field. If you have a bachelor’s degree in computer science, then you can study data engineering at the master’s level. However, it’s possible to master this profession without continuing studies in higher education institutions. For this, 4 stages need to be passed:

Develop skills needed for data engineering

At the initial stage of your career in data science, learn the basics of cloud computing, coding, and database design. Specifically:

    • Collecting databases that relate to business needs
    • Developing algorithms that transform data into practical information
    • Building, testing, and maintaining the system architecture of databases
    • Collaborating with managers to understand company goals
    • Creating new methods and tools for data validation and analysis
    • Ensuring compliance with data management and security policies

Why should you choose data engineering? Working in this field is both enjoyable and challenging. You will play an important role in the company’s success. You achieve this by making data easily accessible to data scientists, analysts, and decision-makers. They need this information in their daily activities. For this, you will need programming and problem-solving skills.

As long as data exists, there will be a demand for data engineers. Moreover, according to a 2019 study, data engineering is the trendiest job in the technology industry. It leaves behind computer scientists, web designers, and database architects.

In addition, data engineering is a high-paying profession – according to 2022 statistics, the average income in the US is $115,176.

To become a successful data engineer, it’s desirable to have relevant knowledge and skills in computer science. This will create the foundation needed in this rapidly developing field. If you have a bachelor’s degree in computer science, then you can study data engineering at the master’s level. However, it’s possible to master this profession without continuing studies in higher education institutions. For this, 4 stages need to be passed:

    1. Develop skills needed for data engineering At the initial stage of your career in data science, learn the basics of cloud computing, coding, and database design. Specifically:
    • Coding: Programming languages are essential for data engineering. Therefore, be sure to learn and develop coding skills. Useful programming languages in this field are SQL, NoSQL, Python, Java R, and Scala.
    • Databases: They are most often used when solving data storage problems. Accordingly, you should be well acquainted with its working principles.
    • ETL (Extract, Transform, Load) systems: This is the process when you transfer data from databases and other sources to one repository, for example, a Data Warehouse. The following tools are used for this: Xplenty, Stitch, Alooma, Talend.
    • Data storage: Not all types of data are stored in the same way, especially when it comes to large amounts of data. When working on solving this problem for a company, you need to understand well, for example, when to use a Data Lake and when to use a Data Warehouse.
    • Automation and scheduling: Automation is an essential part when working with a large database, for which you should be able to write a plan to perform repetitive tasks automatically.
    • Machine learning: This topic is of interest to data science, but it will help you understand the basic principles. It will also show you the need for specialists in this field in the team.
    • Big data tools: Data engineers mostly have to work with large amounts of data. Tools and technologies are constantly evolving. Among them, the most popular are Hadoop, MongoDB, Kafka.
    • Cloud computing: Today, companies are replacing physical servers with cloud services. Therefore, studying this issue well will definitely be useful.
    • Data security: Data engineers often have to work on securely storing data and protecting it. Accordingly, this skill will be needed in daily activities.

Take a data engineering course

Obtaining a certificate will be proof of your skills to employers. Therefore, study data engineering in a certified course and gain relevant knowledge and practical experience. This will help you refine and improve the necessary skills.

Here I’ll also tell you new news – you can now study data engineering at Commschool! If you know the Python programming language, then this program will interest you. Together with a professional lecturer in the field, you will learn to use key technologies and tools for data engineering, design web services for data, and various Python libraries. So, be sure to check out the course syllabus.

Data Engineering

33 Lecture/ 99 Hour / 17 Week

Create a portfolio In the job search process, a portfolio is often a decisive component, as it best shows your capabilities

Therefore, create a web page portfolio of data engineering projects that you have completed independently or as a final course assignment. Place them on your LinkedIn profile or GitHub.

tart working in an entry-level position

Many data engineers start their careers in entry-level positions such as business analyst or database administrator. When you gain experience, acquire new knowledge and skills, you can also get employed in higher positions.

Thus, if you see yourself in this field, take this opportunity and start learning data engineering at Commschool!

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