What Is Data Engineering: A Complete Guide in 2024

Last updated by Nitin Grover on Aug 30, 2024 at 04:59 PM | Reading time: 8 minutes

In this fast-paced world, organizations are increasingly relying on data to gain insights and maintain a competitive edge. As they seek to optimize their data driven strategies, the role of data engineering has gained prominence.

‍‍What is Data Engineering?‍

What is data engineering? It’s a process of collecting data from various sources, transforming it for effective use, and securely storing it to ensure its uninterrupted access.

Data engineers work on data to make it accessible to other stakeholders like data scientists and data analysts to interpret and analyze.‍

Back in 2017, a report by Gartner Inc. stated that more than 87% of data science projects were failing because of substandard data modeling by unskilled resources. As a result, enterprises weren’t able to generate optimal value from the available data.

Soon, the organizations realized the role of skills used to transform and transport data in a highly reusable form to end-users. That’s when the role of data engineers gained prominence.

‍A data engineer handles the technological part of the data infrastructure of a company.

Whereas a data scientist primarily works on extracting insights from available data to assist organizations in big decision making, a data engineer manages the data infrastructure in general or specifically works on maintenance of data pipelines, designing a warehouse, etc.

Professionals planning to elevate their career in data engineering can pursue the Data Engineering course offered by Interview Kickstart, a global leader in career up leveling. The course prepares professionals to clear job interviews in FAANG+ companies.

Hiring managers and tech leads from top IT companies in the world will be your trainers in the course.

So, if you want to pursue a course in data engineering, machine learning, data science or MLOps engineering, Interview Kickstart is the right place for you.

‍

What is Data Engineering? Extract, Transform and Load (ETL) Process

Data engineers play a crucial role in every stage involved to turn raw data into something useful for the other stakeholders to work upon. Typically, the three stages involved in this data journey are Extract, Transform, and Load (ETL) or Extract, Load and Transform (ELT).‍

Data Extraction (Extract). Data can be stored anywhere. To make use of it, a data engineer extracts data from its sources, which can be a database, an ERP system or from public sources made available online

Data Transformation (Transform). Data sourced from various available sources can be raw, unstructured, or may not be of use to an organization in its original form. By performing operations like cleanup, structuring and formatting, a data engineer transforms the data to make it ready to be consumed.

Data Storage (Load). Data engineers store the transformed data in a repository called data warehouse or in more specialized cases, data mart or data lakes. A data mart serves the needs of specific departments in an organization.

‍At times, data may first be loaded in a repository called a lake and transformed into something useful afterwards. This process is called Extract, Load and Transform or (ELT).
‍

In nutshell, the main role of a data engineer is to get the right data to places where it is needed.

What is Data Engineering? Responsibilities of a Data Engineer
‍

Here we look at the functions a data engineer performs during a day in office.

Develop and Maintain Processes: To ensure that the right set of data is fetched and delivered into the right places, a data engineer develops and maintains ETL processes. While doing so, he also implements rules and procedures required to streamline the entire process.

Monitoring of infrastructure: A data engineer’s day in office starts by monitoring and checking the functioning, performance and security of different data pipelines and databases. After all, it’s the role of data engineers to ensure that all stakeholders in an organization get secure access to data on an anytime basis.

Optimizing of infrastructure: A data engineer may also consider to optimize the performance of databases and data resources because working on large datasets takes time and resources. While doing so, he may work upon removal of bottlenecks, resolution of performance issues and scalability limitations.

Cleanup of Data: To ensure that the data that gets delivered to other stakeholders in the organization is of high quality and is free from any problems, a data engineer may perform data cleansing operations on it.

Collaboration and Coordination: As a data engineer facilitates access of data to other stakeholders, during any day at office, he may also collaborate with them to fulfill their requirements.

For example, he might require to grant access to a specific data repository to a data scientist or a data analyst

‍What is Data Engineering: Technical Skills‍

Data engineering is a highly in-demand profession. To succeed as a data engineer one needs to have the following skill sets:

Undergraduate degree in data science, computer science, or any related field
Knowledge of programming languages like SQL, Python and R
Expertise in relational (structured) and no-relational (document oriented) databases
Working knowledge of extract, process and load (ETL) systems and data warehousing
Knowledge of Apache tools like Kafka, Hadoop and Spark
Proficiency in any one of the cloud computing technologies like AWS, Azure or JCP
Knowledge of a few infrastructure tools such as Docker, Terraform and Stallsock.

‍What is Data Engineering: Soft Skills‍

In the data engineering role, a large part of an engineer’s office day goes in collaboration and coordination. So, along with a host of technical skills, he should also possess the following soft skills:

Creative thinking
Problem solving
Ability to communicate effectively
Attention to detail
Time management
Interpersonal relations
Adaptability

Also Learn: How to Prepare for Data Engineer Interviews

‍What is Data Engineering? Responsibilities and Salaries‍

Data Engineering is a highly in-demand profession. Entry-level data engineers begin their journey with a six-digit salary, which can rise up to more than $200,000 as they progress in their careers.

So, what does the data engineering career path look like

‍Entry-Level Data Engineer: Experience (0-1 Years)

Take up small and ad-hoc projects and perform bug fixes, as and when required
Assist their seniors to manage, optimize, and analyze data
Collaborate with other stakeholders to understand data requirements
Stay updated with best practices, emerging technologies, and latest industry trends

‍Junior Data Engineer: Experience (1-3 Years)

Work on activities like data design and building pipelines
Maintain data infrastructures like data pipelines, data warehouses, etc.
Debug applications and adding smaller features to existing resources
Assist senior data engineers to perform root cause analysis and perform remedial procedures

‍Mid-Level Data Engineer: Experience (4-6 Years)

Perform more proactive project management roles
Collaborate with product managers and data scientists to design and build business- and product-oriented solutions

Develop efficient, secure and robust ETL and ELT processes
Identify their niche and acquire skills to build a career around the same

‍Senior-Level Data Engineer: Experience (7-10+ Years)

Manage the development and maintenance of the overall data infrastructure of an organization
Implement and monitor best in class security measures across various data sources
Oversee and mentor the work and performance of entry-level and junior data engineers
Create a roadmap for future data centric initiatives in an organization
‍

Lowest, Average and Highest Salaries of Data Engineers at Various Levels in the US

Source: Glassdoor, Salary

FAQs: What is Data Engineering?

Does Data Engineering Require Coding?
Coding is not a part of day-to-day activity in a data engineering profession. Yet, he must have the know-how to code to solve problems as and when they arise.

Is Data Engineering Stressful?
As there are significant consequences of system failure, the job of a data engineer is stressful and full of challenges. Yet, with challenges come rewards in the form of high salaries and additional benefits.

Can I Become a Data Engineer Without a Degree?
In many organizations, the roles of data engineers often overlap with software engineers. As not every software engineer in this world requires a Bachelor’s degree to succeed in his career, it applies to date engineers as well. So, in nutshell, data engineers do not necessarily require a bachelor’s degree as a basic eligibility.

How many data engineers an organization needs?
A decently sized organization needs 5 data analysts/scientists and one data engineer.

‍Related Articles:

Data Engineering: Building the Foundation for Data Science
Are data scientists paid more than data engineers
The Data Science to Software Engineering Pipeline
Tips: Shift Career Software Development to Data Engineering
"This is how I landed a big data engineer job at Facebook amid layoffs and hiring freezes" — Derek Chung
Data Engineer Resume Guide (Sample Resume Included!)

AUTHOR

Nitin Grover

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What Is Data Engineering: A Complete Guide in 2024

Contents

Nitin Grover

Attend our Free Webinar on How to Nail Your Next Technical Interview

How to Nail your next Technical Interview

Worried About Failing Tech Interviews?

Tools to Enhance Full Stack Development with AI

The Future of Data Science: Emerging Trends and Opportunities

Data-Driven Decision Making: Your Roadmap to Business Success

The Business Impact of Machine Learning: Real-world Case Studies

What is OpenAI? Everything You Need to Know

Mock Interviews for Generative AI: Essential Practice to Land Top AI Roles

Top Python Scripting Interview Questions and Answers You Should Practice

Complex SQL Interview Questions for Interview Preparation

Zoox Software Engineer Interview Questions to Crack Your Tech Interview

Rubrik Interview Questions for Software Engineers

Top Advanced SQL Interview Questions and Answers

Twilio Interview Questions

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