How to Get Started
as a Data Engineer

Refine Your Skills and Remain Relevant

Big data is the backbone of our modern tech experience. Data engineers help make the reams of data more manageable. If you want to learn how to become a data engineer, you should use this guide.

Data engineers use machine learning and more to build data pipelines and organize data. You’ll need to complete several steps to fit the role. This guide can help you work toward becoming an engineer in the data revolution.

What Is a Data Engineer?

A data engineer spots trends in data and builds algorithms that send raw data to the best place for analysis. Data engineers specialize in tools that automatically sort data so it can be analyzed easily.

Data engineers meet data at the beginning of their journey where datasets are cleaned and prepped for data analysts and data scientists. They build data models to chart the data’s path before building data pipelines in Python or other programming languages.

How Does Data Engineering Relate to Data Science?

Data engineering is a branch of data science that makes the rest of the field possible.

Data scientists look at data to answer questions about the future of an organization. Data analysts look at data to answer questions about an organization’s past. It’s up to data engineers to give both sides the data they need to operate.

How Long Does It Take to Become a Data Engineer?

It can take anywhere from two months to three years to become a data engineer. There are education options that take less time, but your path depends on your level of experience in the data field.

You can get a Bachelor’s Degree in Computer Science or a related field if you want to learn at a regular pace. If you’re up for shorter but more intense learning, you may opt for software engineering or data science boot camps that offer data engineering programs.

Where to Study Data Engineering

The best option for learning data engineering depends on your experience and goals in the field. If you’re already working in data analytics and want to add data engineering skills, then you can take a series of online courses to bring those skills up.

If you’re a complete beginner, then you may have to attend an immersive boot camp or a university. If you’re already working as a data engineer, you may want to advance your career by getting a Master of Science in Data Engineering. This can take two years or longer if you take the program part-time.

Whatever your goals are in the field, there’s an option that can cater to your needs.

Data Engineering Universities

Universities offer undergraduate degrees in tech fields like data engineering, computer science, software engineering, and more. They also offer master’s degree programs to further your education.

Overall, pursuing a degree in data engineering may take four to six years. There are less expensive and faster routes to your first data engineering job, but a degree adds legitimacy to your education. This can make your job hunt easier.

Data Engineering Coding Bootcamps

Data engineering boot camps can start your career by skipping the general education classes that take up most of a university student’s first two years. Instead, boot camps jump right into the core courses of data engineering.

These short-term programs offer immersive training and career services to help you launch your career and find a job at a lower cost than traditional schooling.

Data Engineering Online Courses

Massive open online courses (MOOCs) provide the shortest and least expensive path to learning about data engineering. Most of these options are online courses with no additional career support.

Students in MOOCs are those who are either looking to further their knowledge or to just advance their careers. This is because most employers will typically look for a credential before considering you for a data engineering role. These courses are not a replacement for a degree.

How to Become a Data Engineer A Step-by-Step Guide

How to Become a Data Engineer A Step-by-Step Guide

To become a data engineer, you have to learn the tools of the trade and how they fit into your workflow. A solid education lays a good foundation. However, as you gain more real-world experience, you’ll get even better at your job and advance in the field.

Below are the steps you should take to become a data engineer.

Learn the craft

The first step is to study with one of the options mentioned above. Universities, boot camps, and online courses can all teach you the information you need to turn raw data lakes into readable data.

Find on-the-job training

After completing your education, it’s time to test whether you can apply your knowledge to practice. Take advantage of internship programs. Many organizations are always looking for data engineering interns. Bootcamps are also great because they are known for advancing your practical training.

Get real-world experience

After receiving training, you’ll need to secure your first job. Over time, you’ll learn how to do your job more efficiently and in ways that make everyone else’s jobs easier.

Continue your education

There are plenty of professional certificates that you can earn to boost your profile as a data engineer. You can also take online courses at your convenience to supplement your skills.

Decide if you want to get a higher degree

If you want to advance in the field, you may decide to get a master’s degree. Graduate degrees are especially helpful in equipping you with the managerial skills that businesses are looking for. Pursuing one may also increase your salary outlook and job prospects.

Entry-Level Data Engineer Job Requirements

All you need to get your first data engineering job is knowledge of relevant programming languages and data scientist skills. You can get these skills by attending any of the educational options we’ve listed above, and by getting real-world experience in the field after graduation.

Data Engineer Salary and Job Outlook

The average entry-level data engineer salary is about $77,183, according to PayScale. Your first salary will depend on your responsibilities, company, and current skill set. PayScale also reports that the general average data engineer salary is $92,407 per year.

The job outlook for data engineering is strong. According to the Bureau of Labor Statistics, database administrators and related jobs are growing in demand by 10 percent by 2029. This job outlook is much higher than average. There will be more and more data engineering job opportunities in the coming decade.

Example Data Engineer Job Interview Questions

  • What are some of the skills that you think a data engineer should have?
  • Which platforms are you most familiar with as a data engineer?
  • Which programming languages do you most often use?
  • Have you ever worked in a cloud computing environment?
  • Why did you decide to become a data engineer?

What Does a Data Engineer Do?

Data engineers build pipelines that automatically sort data lakes into readable data for analysts and data scientists. They may also tune databases to make them easier for people to analyze. To do their job, they need to build good pipelines and data stores and work with a team to figure out the best ways to sort data.

These three duties will form the core of your data engineering career.

Builds Pipelines

One of a data engineer’s main roles is building data pipelines. These pipelines are more complicated than they may seem on the surface level. In companies the size of Apple or Microsoft, data engineers will be responsible for dealing with petabytes of data regularly.

The pipelines must be built in a way that maximizes usefulness for everyone. You’ll be building algorithms that can quickly analyze and sort massive chunks of data to get people what they need to do their jobs as efficiently as possible.

Builds Data Stores

Data scientists have to turn raw data into useful, readable data. To that end, the algorithms they build have to streamline the process.

Data engineers take piles of raw and unsorted data in data lakes and refine them before placing them in a data warehouse. These are processed and human-readable data storage. This means that the data has to be accessible at any time to anyone who needs it.

Adapts to Change

Data analysts and scientists have different needs depending on the industry. Financial institutions have different needs for their data when compared to a fashion retailer, for example.

No matter where you land as a data engineer, you’ll have to adapt to the industry and be ready for constant change. Needs will change as new projects come in and old ones go out. Because of this, you’ll have to rework old algorithms and introduce new ones regularly to keep your organization ahead of the curve.

Essential Data Engineer Skills and Certifications

Essential Data Engineer Skills and Certifications

Data engineers need to be able to use programming languages, data warehousing tools, and cloud computing architecture. Some of the biggest names in tech offer certifications that verify one’s data engineering capacities.

Once you’ve mastered these skills, you’ll be able to obtain certifications that will improve your job prospects.

Data Engineer Skills

Proficiency in Multiple Programming Languages

The two most popular programming languages for data engineers are Python and SQL. Python is a great general-purpose language that can serve many functions. SQL is a language that’s designed for managing data in relational databases.

On some occasions, you may also have to use R, Java, MATLAB, and more. The programming language you’ll use will depend on your job. That said, it’s good to lay a foundation in Python and SQL when you’re new in the field.

Data Warehousing

As we’ve mentioned above, data warehousing is the act of taking raw data and transforming it into one or more pools of indexed and usable data. There are a few ways to do this, so it’s good to know which works best for your situation.

Amazon Redshift is a tool from Amazon Web Services that’s been one of the more popular solutions for data warehousing. Naturally, Google has its own data warehousing solution in Google BigQuery. Both can handle petabytes of data in seconds, simplifying the sorting process for important data.

Cloud Computing

You’re going to need to borrow some power from the cloud to store the vast amount of data for any organization. A good data engineer has to know how to take advantage of their platform. If you’ve mastered the architecture of a cloud computing framework, it will be easier for your company to handle more data.

Data Engineer Certifications

Google Professional Data Engineer

This certification shows that the holder can design, build, and monitor data processing solutions on the Google Cloud Platform. Google recommends that you have at least a year of experience on the platform before attempting the certification exam.

IBM Certified Data Engineer - Big Data

This certificate is for data engineers who work directly with data architects. Though the exam only comprises 53 questions, IBM offers nine multi-day courses to prepare you to take it.

Microsoft Certified: Azure Data Engineer Associate

This certification shows that the holder can integrate, transform, and consolidate data from structured and unstructured systems to build analytics solutions. To pass this exam, you need experience working on the Microsoft Azure cloud computing platform.

Reasons to Become a Data Engineer in 2021

If you’re interested in building structures that make everyone’s jobs easier, data engineering could be right for you. This is one of the lesser-known roles in the data science field, but the rest of the field couldn’t work without it.

As big data continues to become more important to every organization’s structure, there are plenty of opportunities for entry-level data engineers. This lucrative career could be yours if you have good analytical and math skills.

Data Engineer FAQ

How do you become a data engineer?

You have to get either a degree or a boot camp certificate to learn the tools of the trade. From there, you need to work towards an internship to get the industry experience you need to launch your career.

Is data engineering a good career?

Data engineering has the potential to be a great career if you enjoy the fundamentals of the profession. It can be lucrative and rewarding if you can find a great team to work with that lets you exercise your skills to their full potential.

Do data engineers code?

Data engineers have to code to build the tools and infrastructure that send the data down the pipelines as needed. You’ll need to learn to use Python and SQL at least to get started. You’ll pick up more tools as you progress through your career.

What is a data engineer’s salary?

A data engineer can expect to make around $77,197 per year at the beginning of their career, according to PayScale. The average salary for data engineers who are closer to their peak is around $92,428.

Find the best data science bootcamps to get you hired.


Get matched to top data science bootcamps

By continuing you indicate that you have read and agree to Study Data Science Privacy Policy

Powered By
Career Karma



You don't have permission to register