Please respond to 1) and 2)
1)
Data Engineers are the architects that build and maintain the recourses requires to ensure the flow of data between “outside” sources and “inside” sources is uninterrupted.
Skills
Coding- speak software language to communicate with the programs and computers.
Data warehousing- being able to effectively store the data.
Knowledge of operating systems- being able to use data over appropriate operating systems.
Database systems- how to manage data.
Data analysis- being able to pull 1-4 together to use analytics software.
Critical thinking- being able to think outside the box to develop solutions.
Machine learning- understanding AI that automates analytical models.
Communication skills- effectively communicate your solutions and findings.
Coding Languages
Python- user friendly, easy to learn, best for machine learning.
Java- used for apps and mobile applications, speed.
JavaScript- most popular, developer friendly.
2)
Data engineers are an essential part of the technology industry, and without them, technology would not have the same expertise. There are a few different things that data engineers do and different jobs within the industry. Their main goal is to develop and maintain architecture used in data science projects and ensure that the flow of information between servers and applications runs smoothly. Some of their primary functions are developing data collection processes, integrating new software, and streamlining existing processes. The highest paying engineer job right now is a computer engineer with an average salary of $80,729.00 per year. Next highest paying is a chemical engineer then biomedical.
To be a successful data engineer, there are a few skills that they must have. The skills range from technical and soft skills. First, they must have strong data analysis skills. Without strong understanding of analytics software and what the reports mean, it makes it way more difficult for them to diagnose problems, implement new usage features, and overall improve the process. To go along with that, they must have critical thinking skills. Once they look at the data, critical thinking allows them to approach problems and solutions in a creative and effective way. To give an example, if they see that something is not running right, they may need to completely change their mindset and approach to get it to run right. The last very important soft skill is communication. They must be able to easily talk with their colleagues about everything. They have to share their findings and the things they are thinking. Without feedback from others, it is hard to learn and improve in any industry.
The top programming language they use to work with data is called Python. Python is an interpreted, object-oriented, high-level programming language. It is very effective for Rapid Application Development and for scriipting because there is no compilation step. The program can determine errors on it’s own and then work to solve them. The next programming language is Golang. Where-as Python is object oriented, Golang is procedural and functional. It supports currency and can run up to 30 times faster than Python. They are different, but many people believe that Golang will soon replace Python in all of its functions. To conclude, Ruby is the last one. In Ruby, everything appears as an object and everything is dynamically typed. It is also much more flexible in its features than the other two.
