10 Must have Skills For Data Engineers In 2024

In this world where technologies are increasing day by day, everyone must advance themselves with the demanding skills that are in high demand among the industries. Data engineering is another domain that has been in high demand in the past few years and will increase in the future. Data engineering is the process of developing systems to enable the collection and use of data, and this data is used to enable subsequent analysis and data science.

Therefore, in this article, detailed knowledge has been provided about the data engineer and the must-have data engineer skills in 2024.

Who is a data engineer?

Data engineers are IT professionals who mainly work with multiple settings to develop systems that collect, manage, and convert the raw data into information for data scientists and business analysts to interpret. The main objective of a data engineer is to make the data accessible so that organizations can use it to evaluate and optimize their performance. Data engineers also play a crucial role in building and maintaining databases. Data engineers work with various technologies and tools to ensure that data flows smoothly within an organization.

10 must-have skills for data engineers in 2024

There are multiple skills that a data engineer should possess to grow in their career. We’ll check out the tools and methods that make up the important skills a data engineer needs for a successful career. Some of the most important skills for data engineers in 2024 are mentioned below

1. Big Data Technologies

Big data technology is one of the most important skills that every data engineer should have, as a large amount of data is generated every minute and companies have to deal with that data and store that petabyte-sized data. Apache Spark and Apache Hadoop are the two best tools that are used to handle that data through distributed processing. Both of these tools help in saving on the expenses that are spent on storing such big datasets, and they also offer features that help in effectively analyzing those datasets.

2. Data Warehousing

Data warehousing is another top skill that every data engineer should possess, as businesses have a huge interest in the data. The majority of businesses have started investing in developing data warehouses that collect and store data from multiple sources regularly. Therefore, a data warehouse is something that mainly allows stakeholders to make well-informed business decisions by supporting the process of drawing meaningful conclusions with the help of data analytics. The data-warehousing building process needs a data engineer to perform the data analysis from various sources.

3. Cloud computing tools

The main purpose of data engineers is to handle the raw data of companies and manage that data. This type of company’s data is further hosted on cloud servers. It is important to know about the cloud computing tools needed to work with big data. Some of the most popular cloud platforms are Openshift, Azure, AWS, Openstack, GCP, and so on. There are multiple companies that work with public, in-house, and hybrid cloud infrastructures based on the requirements of data storage.

4. Database Management

A database management system is defined as the foundation of any infrastructure that helps data engineers develop, maintain, and design the overall data infrastructure that supports the needs of companies. Therefore, data engineers mainly choose database management systems, and some of the popular choices of data engineers are Oracle, Microsoft, SQL Server, MySQL, and so on.

5. Machine learning

Machine learning is another important skill that should be learned by the data engineer, as integrating machine learning into big data processing can accelerate the process by uncovering patterns and trends. Therefore, by using machine learning algorithms to categorize the incoming data, transform the data into useful information, identify patterns, and also understand machine learning, a strong foundation in statistics and machine learning is needed. The data engineers should have knowledge of tools such as R, SAS, SPSS, and so on.

6. Data modeling and schema design

Data modeling is defined as the process of developing a conceptual representation of the data that an organization needs to store and analyze, while schema design involves the development of a detailed blueprint of how the data will be organized and structured within the database. The role of a data engineer is to define the relationships between the multiple data entities. Data modeling and schema design mainly involve defining the data types and constraints that will be used to ensure quality and data integrity. It also supports data analysis and reporting by developing logical groupings of data and defining relationships between the data entities.

7. Real-Time Processing

Data engineers should know of data processing frameworks, as these frameworks are mainly responsible for streaming data. Processing large amounts of data is a complex and even more complex task than processing it in real time. Real-time data processing frameworks are mainly used to process data streams and handle the data as it is generated. These frameworks also allow companies to analyze and respond to data in real time, which is very important for applications like monitoring systems, real-time recommendations, and fraud detection.

8. Data visualization skills

Data visualization is another important skill that every data engineer should learn, as big data professionals work with visualization tools. By using these skills, it is necessary to present the information and learnings generated in a consumable format for end-users. Therefore, some of the most popular visualization tools used by data engineers are Tibco, Plotly, Tableau, Spotfire, Qlik, and many more.

9. Data ingestion tools

Data ingestion tools are an important skill that every data engineer should have, as they are one of the most important parts of big data skills. When the amount of data increases, data ingestion becomes more complex, which requires professionals to know the data ingestion tools and the APIs to prioritize the data sources, validate them, and dispatch the data to ensure an effective ingestion process. Some of the data ingestion tools that the data engineers should know are Apache Flume, Apache Storm, Wavefront, Apache Kafka, and so on.

10. AWS Engineering Skills

In the field of data engineering, the importance of AWS data engineering skills is crucial. Therefore, to become an effective AWS data engineer, individuals should know about the multiple services offered by AWS, such as Amazon Redshift, Amazon S3, Amazon DynamoDB, AWS Lambda, and AWS Glue. With the help of these AWS engineering skills, the data engineers are capable of using these services effectively.

Conclusion

Data engineers should possess some of the very important skills that are used by companies to perform better and work effectively. The data engineering skills include strong programming languages with expertise in Java, Python, and so on. The skills mentioned for data engineers in 2024 show how important it is to know about big data, cloud computing, and managing databases. It is really important to keep up with the changes in technology, and being good at data engineering is crucial because a lot of companies need it. Learning and using these skills helps data engineers deal with the growing amount of data in today’s digital world.

FAQs

Who are the data engineers?

Data engineers are the individuals who are responsible for implementing and maintaining the underlying architecture and infrastructure of data storage and generation.

What is the use of data engineering skills?

Data engineering skills are used by companies to design and build systems for storing, analyzing, and collecting data at scale.

What are the top must-have skills for data engineers?

Some of the top skills that every data engineer should know are: data management, data warehousing, data visualization, machine learning, data visualization, and data schema design.