Is Becoming a Professional Data Engineer Worthy?

The professional data engineer is probably one of the most frequently asked questions today. Data engineers take charge of integrating different sets of data and making them talk with one another. They take various responsibilities such as:

Developing applications to exploit this data

Designing interfaces

working with technology platforms such as Hadoop and NoSQL

By contributing to the growth and improvement of their companies' offerings and delivering services, the data engineers also develop an understanding of the way different people use the products and services and this insight drives the next generation of technologies. The companies who are hiring data engineers these days are employing these skills to their advantage.

Professional-Data-Engineer: What is a Data Engineer?

A data engineer is an individual that has a broad understanding of data and how it flows through a software system in order to design and implement new systems, algorithms, and processes. A data engineer can look at an existing product from an engineering point of view and think about how it can be improved or made more efficient.

A data engineer does not necessarily have to understand complex technologies such as database management systems and relational databases, though it would be beneficial for a data engineer to understand these systems as well as basic Java and SQL technologies in order to work on building data systems and systems that can ingest, store and transform various data types.

A Data Engineer is not necessarily just a computer science major, either.

What Type of Data Engineers Are There?

Data Engineering can be broken up into two separate job roles: systems engineers and business analysts. Systems engineers are responsible for building and managing the infrastructure necessary to support the data flows.

Business analysts use the data to drive better business decisions. It is their job to explore, manipulate, and distill the data to make it useful.

How Should I Identify As A Professional Data Engineer?

One way to identify as a professional data engineer is to visit the online database of data engineers. This database was originally launched by Microsoft. The database offers information on what organizations are hiring for, what titles are popular among employers, and job descriptions for the role of a data engineer.

The Role of A Data Engineer

There’s one in every organization, and these IT pros are responsible for what we are calling data. They are what we call data engineers and it's a distinct role within the organization. A data engineer is a professional who's in charge of data infrastructure. They are building and maintaining data pipelines. They are making sure the data gets to the people who need it.

What’s a Data Pipeline?

You can think of a data pipeline like a tanker. The data engineer builds a pipeline, out from data sources, to the right people. The data engineer is responsible for the upkeep of the pipelines so that data in the pipeline doesn’t get corrupted and all the right people get access to the data.

How to Become a Professional Data Engineer

  • Goals of a Professional Data Engineer
  • Data Engineering Criteria
  • Good Hints and Benefits of Becoming a Data Engineer
  • Core Skills of a Professional Data Engineer
  • Functional Skills of a Professional Data Engineer
  • Core Skills of a Professional Data Engineer
  • No. of Credit Hours
  • What About Applications in Data Science, ML, etc.
  • Getting Started in the Field
  • Be Honest and Act Professional

Most of the jobs these days require people to have computer science backgrounds. However, there is a wide range of different requirements. You don't just need a strong computer science background to be a software engineer, but there are still some common pieces of knowledge that you must have to work in data science as well. Here are a few specific pieces of knowledge to get started. Most of the data-driven companies today require someone to be familiar with SQL and NoSQL databases, and this is why you need to learn basic SQL. If you want to work in data science, you don't have to know the entire theory of SQL, but you should be able to do basic queries and create proper index structures.