What is Data Engineer: Role Description,Skills, Background

Data Engineering is one of the booming jobs in 2024, and it is featured in Linkedin’s Emerging Jobs list in the top 15 positions. The data engineering roles are being initiated in all the organizations now, with the vision to integrate a data-driven business module and target customers in an enhanced way. Therefore, data engineering can be one of the best career choices, considering the ongoing technical revolutions and necessities in the market. In this article, we will explore the role of a data engineer in detail, along with their skills and background. Let’s get started with the facts. 

Who is a Data Engineer?

A data engineer is an employee responsible for performing all the data-related software operations and, hence, helps the company understand the analytics based on a data-driven procedure. They collaborate with various members within the organization to create a unique data infrastructure, run various edge-case tests on these designs to separate any errors, and finally update these data systems to integrate all the changes according to company guidelines. 

What are the Data Engineer Roles?

In any business organization, there are mainly three types of data engineering roles that are becoming popular in the current days:

  1. Generic roles: These data engineers are responsible for all the overall data-related requirements within the organization. These employees don’t dive into specialized work portfolios. Instead, they are accountable for everything, from data collection to processing and analysis. These generic roles can be a great option if anyone wishes to switch their career from data science to data engineering. In this way, they will clearly understand the overall data engineering requirements.
  2. Pipeline Specialists: The data engineers working as pipeline specialists work closely with the data scientists. They are responsible for properly using the data collected from various source points. Hence, they must understand distributed systems, IT Technologies, and Computer Science well. These roles are mainly popular with mid-sized companies trying to scale up their operations gradually. 
  3. Database Roles: When organizations diversify their operations, the amount of data they deal with daily becomes huge. In such a scenario, managing these huge volumes of data is a full-time job. Therefore, in these large organizations, several database-oriented roles allow engineers to focus on database analytics. These data engineers must be skilled in data warehousing and have good knowledge of table schema development.

What are the Necessary Skills To Become A Data Engineer?

The necessary data engineer skills one must foster are:

  1. You need intermediate knowledge about programming in various languages like Java, Python, Scala, etc. This will help you build robust data pipelines and automate all the workflows performed on data lakes. 
  2. To efficiently manage large datasets, you must start learning Big Data technologies like Apache Spark, Hadoop, Hive, etc.
  3. To excel in your profile, you must be comfortable handling all types of structured, unstructured, or semistructured datasets. Hence, you should have practical knowledge of relational databases like PostgreSQL and MySQL. Also, learned about NoSQL databases like Cassandra and MongoDB. 
  4. Nowadays, cloud-based data operations are becoming increasingly popular. Hence, the data engineers must have a good knowledge of cloud services like AWS, Azure, etc. 
  5. Another important data engineer skill is to be comfortable with all operating systems, like Linux, Unix, Solaris, Windows, etc., so they can easily operate in all situations.
  6. ETL tools form a crucial part of important data engineer skills. To build robust and efficient data pipelines, you must learn tools like Apache Airflow, Talend, Nifi, etc. You should have good knowledge of the design and management of data lakes. 
  7. To build fault-tolerant data systems, you must understand distributed systems. You also need to know how to scale up these databases and efficiently manage them.
  8. All data engineers must be proficient in Hadoop Technologies, such as MapReduce and HDFS. This becomes helpful when handling huge volumes of datasets.
  9. Real-time data management is an important feature that all data engineers must master. To handle real-time data processing needs, you should master technologies like Apache Kafka. 
  10. Start focusing on Python language coding. These scripts become helpful in manipulating and automating data workflows.

What is the Ideal Background For Becoming a Data Engineer?

To become a data engineer, it is preferred that you have a Computer Science or IT Background. The ideal pathway is to graduate in Engineering with Computer Science fundamentals and then specialize in Data Engineering. Along with the graduation courses, you need to learn programming and coding. It is also recommended that you learn the basics of mathematics and statistics to enhance your work productivity and clearly understand organizational workflows. 

What Soft Skills Do You Need to Master To Become a Data Engineer?

Along with the technical skills, you also need to master various soft skills to excel as an employee and bring out the best results within the organization. You must focus on your communication skill sets and ensure you are highly transparent with all the organization’s members. You must also master communication leadership skills to grow into managerial positions within your company easily. Try to maintain detailed documentation of your work and the goals you must achieve by the respective deadlines. 

Final Words

Data Engineering is a promising sector with great opportunities for young tech enthusiasts. In the near future, all businesses will start integrating data-based modules, and hence, the need for data scientists and engineers will increase. The salary packages for these roles range from $60,000 to $180,000 based on one’s expertise, background, and skill set. So, the best suggestion is to upskill yourself and gradually build practical projects. This hands-on experience will help you better understand data engineering in general and push you beyond your limits to become the best in your field. You can try the online courses and review the documentation to boost your knowledge. If you consistently focus on data engineering skill sets for a year, you can grow as a successful data engineer in a stable organization.