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Learn data engineering with online courses and programs

Every day, digital devices generate an incredible amount of data. Companies need data engineers to process and effectively use data. Learn how to start your data engineer career path with edX online courses.
Data Engineering | Introduction Image Description

What is data engineering?

Data engineering involves the design and building of architectures that harness, store, and analyze data so that companies can easily use it for their business objectives. Now that machine learning and artificial intelligence (AI) are integrated into many data and analytics platforms, there are many data engineering jobs for professionals to pursue. Many industries use data engineers, including retail, healthcare, public entities, the military, manufacturing, and entertainment.

It can also be important to distinguish data engineering from data science. Data scientists analyze data by creating and using different algorithms. Data engineers work with raw data and build the systems for the data scientists and analysts to use.Footnote 1 People can start as data scientists or analysts and then earn data engineering certifications.

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Data engineering course curriculum

Data engineering programs can cover the basics of data analytics, such as the knowledge of cloud computing, data security, and relational and non-relational databases. These topics may be included in undergraduate coursework, or you may take specialized courses separately at any point in your career. You may even be able to find a free data engineer course offered online. You can also explore required prerequisites for data engineering courses online.

Depending on the boot camp, course, or program you choose, you may encounter some of these data engineering concepts and learning objectives:

  • Designing and optimizing design storage using systems like data lakes and data warehouses

  • Creating a data mesh (the data architecture) used on various data and analytics platforms 

  • Learning the details and applications of a specific platform, such as Google Cloud or AWS

  • Building database systems or data pipelines

  • Mastering data modeling

  • Using Azure, Microsoft’s cloud technology, that allows for building large-scale data systems

  • Developing an understanding of data science, research practice, big data, machine learning, AI, and digital transformation

Explore data engineering jobs

There are a range of data engineer jobs that professionals interested in this field can pursue. Here are a few data engineer specializations to consider:

  • Big data engineer: In this generalist role, you’ll determine the best methods for your company to store, access, analyze, and manage large amounts of data, then create the architecture to do so. You may work directly with various teams across the organization to support their data objectives. You may also be responsible for creating a secure storage system that meets your company’s compliance requirements, and setting your company’s best practices and standards for data usage.Footnote 2

  • Machine learning engineer: Suitable for people who enjoy complex coding, machine learning engineers are responsible for creating and using machine learning algorithms.Footnote 3 This means you’ll likely spend a lot of time creating scalable code that improves results the more it runs its algorithms. You may also create systems for applications like facial recognition, search recommendation engines, and speech recognition.

  • Data warehouse engineer: A data warehouse engineer builds back-end data solutions. You’ll build and maintain a data storage method and delivery pipeline and create data tools for data scientists and other stakeholders to use. You may be assigned to a specific non-data team to help them achieve their project goals by building custom algorithms and creating data sets for them.Footnote 4

How to become a data engineer online

A bachelor’s degree in computer science, data science or software engineering all support a focus on data engineering. You may need a four year degree to compete for certain data engineering jobs.

However, if you majored in another subject, you can still develop a foundation for data engineering by taking coursework focused on topics such as:

  • Python

  • SQL basics

  • Apache Hadoop and Apache Spark, two programs that provide a data processing framework

  • ETL (Extract, transform, and load) tools

  • C++

You can also enroll in online coding boot camps or boot camps in other disciplines such as data science, which will help you gain relevant skills. Remember that every job is different, and the time it takes to complete all your requirements will vary depending on the institution, your knowledge base, and the time you’re able to devote.

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Frequently asked questions

Data engineering is important for many large-scale enterprises today — public and private, in industries ranging from healthcare to utilities to the military, and many more. Without data engineering, companies would be unable to use the enormous amounts of data they collect from digital devices. Data engineers possess the skills to create and maintain data and analytics platforms for companies to access, use, and store data, as well as the ability to create custom data models.

To learn data engineering, you can pursue a bachelor’s degree in computer science, software engineering, data science or a related field, which can require four years of learning, or you can take independent coursework and certifications to learn data engineering. Data engineering certifications may take weeks or months to complete, depending on how much time you have to take courses and the exact program offerings. You can find data engineering programs, courses and certifications offered both online and in-person.

Data engineers are well-versed in coding, particularly Python and C++. They also have foundational skills in program suites like Apache. A prior knowledge of basic data architecture and how to create a data warehouse, build a data pipeline, and otherwise manage data, is also helpful.

If you’re adept at programming, being a data engineer may not be any more difficult than learning any other software discipline. Learning solid math skills can be helpful since certain roles in data science and engineering often requires that you write mathematical algorithms.

It may take you many years to study to become a data engineer, because most engineering jobs require a bachelor’s degree.Footnote 5 If you’re getting a certificate or taking courses to become a data engineer after you earn a degree in another field, it could take a year or two of further study. You may have to complete foundational classes in addition, which will add time.

A data engineer deals with the back end of data which involves building architectures for a company. This allows them to harness large amounts of raw data and decide on security governance protocols. A data scientist is a front-end role, analyzing the data and creating models used for specific project purposes.

A software engineer is a general title for someone who knows how to program, and could be applicable to many roles in the technological field. A data engineer is a specialty software engineer who works with data, enabling companies to use the large amounts of data they receive. Data engineers and data scientists know how to create mathematical algorithms, while general software engineers may not need to use much math in their daily roles.

Once you’ve completed a degree or certificate in data engineering, you can apply to data scientist jobs, data analyst jobs, or data engineer jobs. There are many specialty roles in data engineering, including being a machine learning data engineer, a big data engineer, a data warehouse engineer, or a solutions architect.