Data Engineering: What Data Engineers Do & How to Start Your Career

Big data changes business operations. Companies now need data engineers. These professionals collect and manage large data quantities. Data engineering is the practice of building systems. These systems collect, store, and analyze data at scale. This broad field applies to almost every industry.

Organizations gather massive amounts of data. They need the right people and technology. This ensures data is usable for scientists and analysts. Data engineers make data scientists’ lives easier. You can make a real difference in this career. Fields like machine learning rely on processed data. Data engineers successfully process and channel that data. You will learn more about data engineers here. Discover what they do, their earnings, and how to join this field.

What Exactly Does a Data Engineer Do?

Data engineers build data collection systems. They manage and convert raw data. They turn raw data into information data scientists can use. Their main goal is data accessibility. Organizations use accessible data to improve performance.

Common tasks for a data engineer include:

• Acquire datasets matching business needs.
• Develop algorithms to transform data into useful information.
• Build, test, and maintain database pipeline architectures.
• Work with management to achieve company goals.
• Create new validation methods and analysis tools.
• Ensure compliance with security policies.

Smaller companies often hire generalists. They handle a variety of data tasks. Larger companies dedicate engineers to specific roles. Some focus only on building data pipelines. Others manage data warehouses. They populate the warehouses with data. They create table schemas to track storage. You can Read Our Blog for more insights on data roles.

Data Engineer vs. Data Scientist

Data scientists analyze datasets. They find knowledge and insights in the data. Data analysts perform similar tasks. Data engineers build the required infrastructure. These systems collect, validate, and prepare high-quality data. Engineers prepare the data; scientists interpret it.

Data Engineering Career Outlook and Salary

This career is both rewarding and challenging. You play a vital role in company success. You provide easy data access to decision-makers. You rely on your programming skills. Your problem-solving skills create scalable solutions. Demand for data engineers remains strong. Data must be processed, so engineers will always be needed.

The World Economic Forum projects massive job growth. Data engineering is a top growth job through 2030. LinkedIn listed data engineers as a top job in 2021. Data engineering also pays very well. The average US base salary is $106,966. Some engineers earn up to $164,000 yearly (Glassdoor, April 2025).

Career Path and Advancement

Data engineering is often not an entry-level role. Many professionals start as software engineers. Others begin as business intelligence analysts. You can advance into management roles. You might become a data architect later. Other paths include solutions architect or machine learning engineer. If you need tools for your journey, Shop Our Products now.

How to Become a Data Engineer: Required Skills

You need the right skills to succeed in data engineering. Many data engineers have a bachelor’s degree. Computer science or a related field is common. A degree builds a strong foundation. A master’s degree helps you advance your career. It can unlock higher-paying positions.

You must learn the fundamentals first. Start with cloud computing basics. Learn coding skills and database design.

Essential Technical Skills

• Coding: Proficiency in coding is essential. Practice languages like SQL, Python, Java, R, and Scala.
• Databases: Databases store most data. Be familiar with relational and non-relational databases. Understand how both systems work.
• ETL Systems: ETL means extract, transform, and load. This process moves data into a single repository. ETL tools include Xplenty and Talend.
• Data Storage: You must design smart storage solutions. Know when to use a data lake. Know when to choose a data warehouse.
• Automation: Automation handles large data volumes. You must write scripts to automate repetitive tasks.
• Cloud Computing: Companies increasingly use cloud services. You need cloud storage knowledge. Study AWS or Google Cloud concepts.
• Data Security: You must manage and store data securely. This protects sensitive data from theft or loss.

Certifications and Portfolio Building

Certifications validate your skills to employers. Preparing for an exam boosts your knowledge. Options include the IBM Certified Data Engineer or Google Cloud Certified Professional Data Engineer. Check job listings. See which certifications employers frequently require.

A portfolio shows employers what you can do. Showcase independent projects or coursework. Use a simple website or GitHub. This proves your technical abilities clearly.

Education and Background

A degree is common but not mandatory. Sixty-five percent of data engineers hold a bachelor’s degree. Twenty-two percent have a master’s degree. You might need a degree later for career advancement. Consider majoring in computer science or software engineering. Some programs offer data engineering concentrations.

FAQs About Data Engineering

Is data engineering a good career?

Yes, data engineering is an excellent career path. It offers high salaries and strong job security. The BLS projects 8% growth through 2032. This adds thousands of new jobs yearly.

Do data engineers code?

Yes, data engineers must code. They frequently use Python, Java, R, SQL, and Scala.

Can data engineers work remotely?

Many data engineers can work from home. The nature of the work often allows for flexibility. Some employers may still require on-site presence.

Reference: Inspired by content from https://www.coursera.org/articles/what-does-a-data-engineer-do-and-how-do-i-become-one.