In recent years, the data has been growing exponentially. Business needs new, more efficient ways to work with them. They need powerful data platforms and employees who optimize processes and supply prepared data for other specialists. A data engineer is a specialist who helps to collect, store, and process such data.
Who is a Data Engineer
The need for data engineering grew along with how large companies accumulated user data. Information had to be collected, processed, and structured before beginning to analyze and search for insights.
After the 2010s, large corporations needed to pay more attention to knowledge about users and insights searches because it directly affected their income. Therefore, new tools and approaches appeared at each stage of working with data, and a technological stack developed.
The data analyst could no longer maintain proper skills in all areas, so this universal profession began to split into separate specializations. So the job of data engineer stood out in an independent direction.
So, a data engineer creates or configures the software for data collection, cleaning, transformation, etc., and further use in the business.
Duties of Data Engineer
The responsibility of a data engineer is to build a reliable and effective architecture for working with data. He configures and maintains systems for data processing, creates pipelines for loading data from various sources, and cleans and filters incorrect information.
The data engineer knows how different parts of the architecture interact with each other. He should be able to integrate them and build a complete process, from collecting raw data to communicating the analysis results to the customer. The data engineer should understand the technologies' possibilities and limitations.
Suppose a company wants to collect and store more data to make decisions based on them. In that case, the work of a data engineer is to understand whether the existing architecture is suitable for these tasks or whether something needs to be changed: add computation resources, integrate new tools, or completely rebuild the architecture.
Another aspect of the data engineering profession is data preparation and cleaning. Data engineers work with raw data, which may be incomplete, contain errors, or are unsuitable for solving a problem. They prepare data for further processing: automate the collection, data cleaning, and transformation into a species ideal for analysis.
Although the responsibility of a data engineer is to work with data, he looks at it in terms of structure, storage logic, and processing efficiency. He is responsible for ensuring that the data is suitable for further processing. The data engineer provides the availability of data: the final architecture should allow users to quickly access the data and receive a response to the request. At the same time, he does not analyze business information in this data.
What does a Data Engineer do?
designs, develops, and maintains a big data architecture
configures data collection from disparate sources to a single repository
checks the data for correctness, discards incomplete or erroneous data
leads the raw data to a type suitable for further processing and analysis
creates pipelines for loading and processing data
is looking for new opportunities to improve data collection and processing.
Qualification of a Data Engineer
knowledge of the SQL query language at a level not lower than Middle;
knowledge of the Python programming language (data collected, interpreted with it);
experience with cloud platforms and have the corresponding certificates (Amazon Web Services, Microsoft Azure, and others);
knowledge of the SQL and NoSQL database system;
programming languages Java/Scala;
knowledge of one of the BI tools: Power BI, Tableau, etc.
Why Data Engineer is Useful to Business
Data engineers develop solutions, data pipelines, data architecture, etc. They create jobs that extract data, clean it, deliver it to destinations, etc. Their task is to create software that will work with data.
Data engineers receive data from different sources, including from the database. It can be SQL Server, Oracle DB, MySQL, Excel, or any other data storage or processing software. After that, they apply algorithms to this data and make it worthwhile so that it can help different departments, such as marketing, sales, finance, and others, improve their work performance.
Data engineers do the following for the business:
сollects product and/or customer information from multiple sources
sorts and processes information so that it can be handled further
securely stores data.
A Professional Date Engineer should have a certificate. Now the world is moving toward big data, and the certificated data engineers can manage it to create accurate forecasts.