What is data engineering? This is probably the first question that comes to your mind after reading this title. Data engineering is simply the acquisition, storage, transformation and management of data. This ranges from simple data analysis to writing complex data processing models and algorithms to manage Big Data. Data engineers are the most technical profile in the field of data science, serving as a critical bridge between software and application developers. They are responsible for the first step of the traditional data science workflow, namely the process of collecting and storing data. They ensure that large amounts of data collected from various sources become resources that can be accessed by other data science professionals, such as data analysts and data scientists. The most important skills of a data engineer include:
- - Be proficient in programming in languages such as Python and Scala. - Learn automation and scripts
- - Understand database management and develop your SQL skills
- - Master data processing system
- - Learn how to organize your workflow
- - Expand knowledge of cloud computing and platforms such as AWS
- - Increase your knowledge of infrastructure such as Docker and Kubernetes
Programming skills in Python, R and/or Scala and database management are the core skills of any data engineer, as you will use them 75% of your time. Therefore, it is very important to learn these skills. According to many studies, data engineering is a growing field that holds great promise for those willing to enter. Below is a review of recent studies on advancements in technology.
Data engineering is an emerging profession and it is not always easy for recruiters to find the right candidates. Competition for this hard-to-find talent is high among companies, resulting in some of the highest salaries among data science positions. Based on several career portals, the average salary for data engineers in the United States is $114,564. However, these numbers differ depending on where you work in the country. So, for example, according to Glassdoor, the average salary for a data analyst in New York is $120,637, while in Chicago it is $113,610 and in Houston it is $94,416.
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