A Data engineer is a specialist who works with large amounts of information using different technologies. It forms a reliable infrastructure for working with data. Data engineer collects data, analyzes, and organizes.
A data engineer can create a system that will store reports on the company’s analytics for a certain period. Such a system will collect data from different sources, keep it in the desired form, and process it so that the end user can figure it out. Data Science Training does help students and professionals get proficient in the field and learn in-depth about its concepts.
The specialist also carries out the following job duties:
- analyzing data and applying machine learning algorithms
- working with various data sources
- creating dashboards
- working with frameworks (software platform)
- organizing and conducting A / B testing
- writing recommendation systems
- solving business problems associated with fast information processing
- using different programming languages while working.
Keep in mind, all of the duties mentioned above are only the essentials. From this list, we can assume that data engineers are specialists in software development.
For example, if a company starts generating a large amount of data from different sources, your task as a data engineer is to organize the collection of information.
The list of instruments used in this case may differ; it all depends on the volume of this data. Most companies do not deal with big data at all, you can use a SQL database (PostgreSQL, MySQL, etc.) with a small set of scripts that send data to the storage.
The professional skills of a data engineer include:
- ability to program in Python
- knowledge of libraries NumPy, Pandas
- data visualization with matplotlib
- knowledge of probability theory and statistics
- experience with Machine Learning
- ability to work with neural networks
- ability to work with semantic segmentation
- knowledge of databases MongoDB, PostgreSQL, SQLite3.
Data Engineer has the following personal characteristics:
- analytical mind
- desire to learn new things
- the ability to quickly switch between tasks.
Pros and cons of the profession
There are positive and negative aspects while working as a data engineer.
- high salary
- the ability to work remotely
- constant development.
- sedentary and painstaking work;
- professional burnout.
How to become a Data Engineer?
Such specialists require high-quality training, as they work with data that is important for the company. It is tough to master the profession from scratch on your own. You need to read a large amount of literature, learn a programming language, deal with libraries and frameworks. This direction is definitely what you cannot do without an excellent theoretical part and an experienced mentor. Learning will bring the desired result if it is structured and supported by practice.
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