What does a Data Engineer do?

With massive amounts of data generated through our activities over the Internet, it has become crucial for businesses to process this data to make sense of it. Can you guess how much data is generated in a day across the world?

It’s 2.5 quintillion bytes.

Isn’t it incredible?

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.

What is Data Engineering?

Data Engineering is a subset of data science which is an umbrella term that encompasses various fields of knowledge for working with data. Data engineering requires you to create and manage the technical infrastructure of a data platform. As a Data Engineer, you are required to build algorithms to provide easier access to raw data.

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.

Responsibilities of a Data Engineer

Apart from extracting hidden insights, data engineers are now concerned with the management of data as well. Data engineers establish the foundation of a database and its architecture. They assess various requirements and seek for relevant database techniques to build a robust architecture. Then data engineers are required to develop the database from scratch by beginning with implementing the architecture. As a data engineer, you have to test its performance and try to debug the issues, if any. Now comes the maintenance of the database to ensure that it is working steadily without causing any disruption. When large-scale systems are concerned, you need to be an expert in managing those systems as it requires continuous maintenance for overseeing scalability and performance issues.

You are also expected to assist the data science team by developing dataset procedures to help in data mining, modeling, and preparation. So, data engineers play a crucial role in improving the quality of data.

To summarize, the primary responsibilities of a data engineer are:

  • Develop, establish, test, and manage database architectures
  • Line up architecture with business objectives
  • Data acquisition
  • Developing data set processes
  • Leverage programming languages and tools
  • Carry out research for requirements of industry and business
  • Identify hidden patterns using data
  • Utilize huge datasets to address issues of the business
  • Determine ways to enhance data reliability, quality, and efficiency
  • Employ sophistic analytics programs, statistical and machine learning models
  • Assemble the data for prescriptive and predictive modeling
  • Automate the tasks that are tedious to eliminate manual participation
  • Deliver updates to business partners and stakeholders based on analytics.

How Data Engineers help organizations?

Data engineers collect and extract data from different sources, including the database such as SQL Server, MySQL, Excel, OracleDB, or any other data storage and processing software. Next, they apply algorithms or processes to this data to make it useful for various departments like finance, marketing, sales, and others to improve their work productivity.

Data engineers bring velocity to the data and supervise the analytics in an organization. Data engineers help businesses find estimates like fraud, churn, and customer relations, thereby enabling them to make real-time decisions. 


As the world is moving steadily towards Big Data, data engineers skilled, trained, and certified can provide well-governed data pipelines, make accurate predictions, and eventually improve machine learning and data models.

To become a successful data engineer, you should take an online training course and get certified. The online training course makes your study go smooth and trouble-free, and to ensure that you are well-prepared, doubt sessions are carried out at the end of the training. Usually, doubt sessions are carried out by industry experts so that the level of your training is up to the mark. Enroll yourself now!

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