What does a data engineer do?


GUEST NOTE: The past few years have seen a paradigm shift regarding data and related fields. In addition to retrieving meaningful information, data management has become equally important in the digital age. Big Data is constantly revolutionizing the way businesses do business. Finally, the demand for data engineers is continuously increasing.

With the increasing amount of data being generated every second, managing and processing this massive amount of data has become crucial. In this way, the roles of data workers are changing and growing at lightning speed.

Quick bites:

  • The global big data and data engineering services market is expected to grow from USD 130.7 billion in 2020 to USD 234.6 billion by 2025, growing at a compound annual growth rate (CAGR) of 10.2% according to data from Global Industry. Analytics Inc.
  • According to the US Bureau of Labor Statistics, there will be 11.5 million new job openings for roles related to data science and analytics.
  • A recent report from Dice Insights indicates that there is a whopping 50% year-over-year growth for data engineering roles
  • According to Glassdoor, the average annual salary of a Data Engineer fluctuates between 8 lacs and 20 lacs
  • Some of the biggest names looking for data engineers include Microsoft, Capgemini, Deloitte, Facebook (now Meta), Apple, Walmart, Google, Amazon and many more.

These are some of the reasons that ensure that a career in data engineering can be rewarding and lucrative. Many data professionals who want to advance their career in this field prefer to pursue a data engineering postgraduate program that helps them land their dream career.

Let’s review data engineers and their job descriptions.

What is a Data Engineer?

A data engineer is an IT professional who typically prepares data for analytical and operational use. As a data engineer, you typically have to work with different parameters to develop systems that can collect, manage, and transform raw data into insights such that it becomes usable for data scientists and analysts.

Basically, a data engineer defines the foundations of a database and its architecture. You need to evaluate various requirements and select relevant solutions to build a robust architecture. Then you need to start the implementation process and create a database from scratch. You should monitor performance issues at regular intervals to make sure everything is working properly.

A data engineer’s expertise is valued when managing large-scale processing systems where scalability and performance issues require consistent maintenance.

By building data set procedures, a data engineer can help data analysts and data scientists with data mining, modeling, and production processes.

Roles and Responsibilities of a Data Engineer

The most crucial goal of a data engineer is to make data accessible to relevant organizations and users so that it can be used to assess and optimize their performance. Let’s look at some of the typical roles and responsibilities you’re expected to take on as a data engineer.

1. Build and maintain the data architecture

You need to take a systematic approach to planning, building, and maintaining data architectures while ensuring they are properly aligned with all business requirements.

2. Data collection

To work with data, it must first be collected from the right sources. To start working with databases, you need to formulate a perfect set of dataset processes and optimize the data.

3. Research

Typically, to troubleshoot while dealing with business issues, you need to research common trends and patterns.

4. Improve skills

You must be able to work in any deployment environment, regardless of the programming language used. So, you should be open to upgrading yourself and ready to improve yourself, because a career in the world of technology requires constant upgrading.

As a data engineer, you should be familiar with machine learning and some of its popular algorithms including k-means, decision trees, random forest, and many more.

You are expected to be proficient in data analysis tools such as Tableau for data visualization, Apache Spark, and Knime. These tools are typically used by data engineers to gain valuable insights into all types of industries including healthcare, finance, banking, logistics, media and entertainment, etc.

5. Build Patterns to Identify Patterns

As a data engineer, you need to use a descriptive data model for aggregating data to get useful insights. You may also need to build predictive models to use forecasting techniques to gain insights into the future.

Apart from these models, you can use prescriptive models when you want to provide recommendations for different outcomes and help your users. Thus, a large part of the time is devoted to identifying the hidden information from the stored data.

6. Automation of tasks

Data engineers spend most of their time diving deep into data and pointing out tasks that can be automated and eliminate human intervention.

To summarize, the tasks you need to accomplish as a data engineer are:

  • Build datasets to align with predefined business requirements
  • Create algorithms capable of transforming data into actionable and useful information
  • Develop, test and manage database pipeline architecture
  • Develop the latest data analysis tools and data validation methods
  • Collaborate with senior management to understand the organization’s objectives
  • Ensure security policies are compliant with data governance


To pursue a career in data engineering, you need to learn coding skills, learn ETL techniques, work with relational and non-relational databases, cloud computing, machine learning, big data tools, and security. Datas.

To acquire these skills, you can take online training and learn about all the tools and techniques needed to become a successful data engineer. Many online courses allow you to learn at your own pace and allow you to choose from different learning modes (e-learning, instructor-led, and blended). Plus, you’ll have the opportunity to participate in real-world projects that will give you hands-on practice with the tools.

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