Data Engineer

According to Dice’s report, businesses are looking for Data Engineers with great eagerness. It also reported that the hottest tech job of 2019 was that of a Data Engineer as the number of job openings for the same grew by 50% year-on-year.

According to Payscale, the average annual salary of a Data Engineer at mid-career is around USD 92,352 and can go as high as USD 130,000.

We have always read that the raw data is converted into a user-readable format so that business board members can make strategic decisions. Actually, the journey of raw data into analytical boards is not so simple. A dedicated ecosystem is required to systematically process the data, referred to as a data pipeline. Data pipelines are built up of techniques that form a specified environment where the data is collected, stored, processed, and queried. In addition to data scientists, some data engineers serve as the architects of data platforms.

Do you want to make a career in such a highly in-demand domain and is paying great as well? Let us discuss all you want to know about a Data Engineer job description and how a Data Engineer certification can help you in landing a career that is shining bright.

Who is a Data Engineer?

Put simply, data engineers are crucial members of a company’s data analytics team, who is responsible for managing, optimizing, supervising, and controlling retrieval of data, its storage, and distribution throughout the organization.

The Role of Data Engineer

The three main roles that a Data Engineer may be required to play are:

• Generalist

Generalists are usually found in small firms or small teams. They are accountable for every step of data processing, from collecting to managing to analyzing it. When small firms are concerned, you need not worry about ‘scale,’ so it is a wise move to transition from data scientist to a data engineer.

• Pipeline-centric

These are generally found in mediocre companies where a data engineer has to work in parallel with a data scientist to help make the data valuable and meaningful. As a pipeline-centric data engineer, you are required to have a detailed knowledge of distributed systems and computer science.

• Database-centric

The name itself clarifies that this role is meant for larger organizations where it is crucial to managing the flow of datasets. So you are required to focus on the analytics databases. Generally, database-centric data engineers work with data warehouses covering multiple databases and are also accountable for developing table schemas.