How to Become a
Data Engineer
Best Education Tracks, Key Skills, and Top Certifications
Data engineering is one of the most in-demand roles in organizations today. Data engineers help companies draw insights from data and make decisions. This goes a long way in turning around a company’s financial or growth outlook.
Data engineers construct data pipelines and set up processes that help them analyze data continuously. Like data scientists, they need specific skills and education to get a job. This guide can teach you how to become a data engineer with all the information you need to know.
What Is a Data Engineer?
Data engineers are people who are skilled in collecting, storing, and processing data. They are proficient at choosing proper data storage methods, defining efficient pipelines to yield good results, and leveraging technology to draw relevant insights.
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Data engineers use modern technologies like distributed computing, the cloud, machine learning, and artificial intelligence to gain the best results.
What Type of School Should You Attend
to Become a Data Engineer?
To become a data engineer, you should attend a university and get a bachelor’s degree. A data engineer’s daily routine involves handling and managing data with computer systems. Therefore, most organizations look for a bachelor’s degree in a computer-related field. Bootcamps and online courses can also help you gain relevant skills.
Best Data Engineer Education Tracks
Ranging from a traditional degree to a self-taught online course, there are multiple pathways to this profession. Here are some of the best education tracks to become a data engineer.
Data Engineer Degrees
A Bachelor’s Degree in Data Science or a computer-related field is almost mandatory to secure a job as a data engineer. This is because the role requires you to handle numbers on a large scale and implement operations to complete the required job.
Additionally, a master’s degree in a relevant field helps build a firmer grasp of various data engineering topics. It proves to the employers that you are a premier professional. This is a good choice if you want to get a high-paying job in data science.
Data Engineer Bootcamps
Bootcamps are a significant contributor to the pool of technical professionals in the industry. These intensive programs are helpful for those who are looking to switch to data engineering from non-technical roles. They are available in all timeframes and categories, which means you can enroll at a boot camp while you have a full-time job.
Check out one of our guides on choosing the best data science boot camp to start your learning journey. Bootcamps are a great choice because they are less expensive and take less time than traditional degrees.
Data Engineer Courses
Another great way to enhance your data engineering skills is to take up online courses. They can focus on theoretical knowledge and aid your learning journey with hands-on projects. The projects are often guided every step of the way by the instructors, so you can get help if you get stuck at any point.
How to Become a Data Engineer: A Step-by-Step Guide
Data engineers need to be seasoned professionals, so they need lots of training. Below are a few simple steps to enter a data engineering career.
Earn a bachelor’s degree
As mentioned earlier, most companies look for a bachelor’s degree in a computer-related field like computer science, so the first step involves securing a degree in relevant domains. You can also start with an associate degree.
Build your skills
Once you attain the required degree, the next step is to build on your practical skills. Analysis and engineering are two pillars of data engineering for data sets. You need to take up courses or work on personal projects to ensure confidence in these skills.
Look for an internship
Entry-level jobs or internships are a great way to gain on-job experience and boost your resume. Many employers offer unpaid and paid internships to help candidates achieve a solid grasp of the role’s responsibilities.
Acquire relevant certifications
You also need to gain certifications or licenses to attest that you have what it takes to make a good data engineer. These will ramp up your resume and impress employers.
Pursue higher education
If you are willing to go the extra mile, you should consider pursuing a master’s degree to widen the spectrum of jobs you can apply for as a data engineer.
Key Data Engineer Skills
If you wish to become a successful data engineer, you must possess a specific set of skills. This includes being able to assess the potential of a dataset and create a plan to analyze it. However, you need to know certain technologies to complete these tasks.
Below are some of the critical skills that you should possess to become a successful data engineer.
Database Systems
A data engineer is expected to work with data that can be structured or unstructured. If structured data is encountered, one of the most basic ways to store it is in a database. Therefore, you should have good knowledge of popular database systems such as SQL or MongoDB to store and use structured data faster.
Distributed Systems
More often than not, data engineering requires handling vast tracts of data. It is often wise to break this down into decentralized processing via distributed systems. Apache Spark and Hadoop are two of the most popular distributed data processing technologies. You need to be familiar with both of these to adopt any solution to solve problems.
Machine Learning
Once you have data at hand, you are required to draw conclusions and insights from it. Multiple tools can help you draw basic statistical insights, but there are times when the predictive analysis is helpful. Machine learning can help you analyze data trends and provide insights that are not directly offered by the given data.
Data Engineer Salary and Job Outlook
According to the Bureau of Labor Statistics (BLS), employment opportunities in computer-related fields will increase by 15 percent by 2029, which is much faster than the average projected growth rate. This means that data engineering and other related careers will see significant job demand and good growth in this decade.
PayScale suggests that data engineers earn an average salary of $92,407 per year. This is a great number, and it can get even higher if you have more experience and education.
Min salary
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Average salary
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Top salary
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Entry-Level Data Engineer Job Requirements
Most entry-level data engineer jobs require academic proficiency in data processing and manipulation techniques. You should have a degree and internship experience under your belt to help you get a job. According to PayScale, entry-level data engineers make $77,183 per year.
What Does a Data Engineer Do?
A data engineer performs many different tasks while working with data. It is a strategic role with many responsibilities attached. The tasks span from developing data storage designs to deploying processes that filter glitches from the data. Below are a few of the significant responsibilities of a data engineer.
Develops and Manages Architectures
The first step to processing data is to store it efficiently. Data engineers are expected to design and provision data stores, or lakes, to help them access and dump data faster. In many cases, a simple data lake does not suffice. This is where data engineers are expected to design complex architectures to maximize the output of results.
Acquires and Analyzes Data
Acquiring the correct data can be a challenging task. Data engineers are expected to find viable data sources and chart out processes that can ensure an economical collection of data. They also draw insights from the acquired data. You need to be well-versed in data visualization, machine learning, data modeling, and much more to cover all of these tasks.
Conducts Research for Business
The primary reason companies collect and analyze data is to inform their business practices. Data engineers are critical in this process. You need to be prepared to carry out research based on the available data, look for more sources if required, and then present the results for the relevant problems at hand.
Data Engineer Certifications
Certifications help add authenticity to your professional profile. In the case of data engineering, certifications help you make a strong impression in front of your potential employers by proving that you have an exceptional understanding of how to handle data.
Below are some of the most popular certifications among data engineers.
Cloudera Certified Professional (CCP): Data Engineer
The CCP certification is a hallmark of a candidate’s ability to handle core operations in Clouder’s CDH environment. It focuses on ingesting, storing, transforming, and analyzing data using CDH. This is a great certification if the organization that you are applying to uses Cloudera internally.
Cloudera Certified Associate (CCA) Spark and Hadoop Developer
This credential certifies the core skills you need to ingest, transform, and process data using Apache Spark and Cloudera. Apart from being skilled in Cloudera’s technologies, you are also certified to be an expert at building Hadoop applications using Apache Spark. These big data skills are easily transferable to other platforms if needed.
Amazon Web Services (AWS) Certified Data Analytics – Specialty
The AWS CDA credential certifies your technical skills in AWS-based data lakes and analytics. It validates a candidate’s ability to operate AWS data analytics tools and understand the underlying integrations between them.
How to Prepare for Your Data Engineer Job Interview
Data engineering job interviews are focused on assessing your knowledge of data management and implementations in a real-world scenario. You may be quizzed on the theoretical aspect of data management, such as the various ways of analyzing data, the technologies that can process data faster, and more.
Below are some of the most common questions asked in data engineer job interviews to help you ace your interview.
Data Engineer Job Interview Practice Questions
- What is data modeling?
- How do you distinguish between structured and unstructured data?
- What does HDFS mean?
- Can you explain Hadoop streaming?
- What is your troubleshooting process?
How Long Does It Take to Become a Data Engineer?
Since becoming a data engineer involves a bachelor’s degree, it takes around four to six years. However, if you already have a relevant degree, a couple of months of fundamental courses can give you the training you need.
Associate degree
years
Bachelor’s degree
years
Master’s degree
years
Should You Become a Data Engineer in 2021?
Yes, you should become a data engineer in 2021. Data is one of the most valuable possessions in the contemporary world. Increasing numbers of companies are using data to guide their business operations towards success. Therefore, 2021 is the best year to enter this field.
With excellent career growth prediction and handsome salary packages, a data engineer is one of the best roles to enter in 2021.
Data Engineer FAQ
Which languages do data engineers use?
Data engineering is more about handling data than about working with languages. This is why data engineers do not use a fixed set of programming languages. However, going by popularity, Python and R are both used by data engineers.
Is data engineering stressful?
Data engineering is about making data talk. If you are not good with numbers, this job can be stressful. In most cases, a basic refresher on mathematics helps engineers understand and visualize trends to reduce stress.
Do data engineers use C++?
While C++ is not the most popular language among data engineers, many use it for its simplicity and speed. C++ is one of the fastest languages, which helps carry out operations on large datasets.
What degree do data engineers need?
As a data engineer, you should have a Bachelor’s Degree in Data Science or a related field. This can help you learn all the information you need to become a data engineer. However, you can also follow alternative paths.
