How to Become
a Big Data Engineer
Education Pathways, Skills, and Certifications
If you are looking for a lucrative tech career that combines engineering, software, and data science, big data engineering is the way to go. This comprehensive guide can teach you everything you need to know about how to become a big data engineer.
Read below to learn more about this lucrative tech career. We will include the education pathways, industry-required skills, job preparation information, and certifications needed for this job.
What Is a Big Data Engineer?
A big data engineer is a tech professional who develops, maintains, and tests big data infrastructures. Infrastructure refers to software systems that store, collect, and process large volumes and a variety of data.
A data engineer is responsible for ensuring the data architecture is always working well. The architecture should be ingesting, managing, and allowing proper data access to the company.
The job duties of a big data engineer and a data scientist are similar but have a few key differences. Although both professions deal with data architecture, a data engineer focuses more on the development of the infrastructure whereas. A data scientist focuses more on data analytics and interpretation.
What Does a Big Data Engineer Do?
A big data engineer performs many tasks on the job. Now that you know the basics of the job, let’s discover more about their job duties. The responsibilities lie in a wide range across the spectrum.
Designs Software Systems
Having a background in software engineering is essential to this career. One of the primary roles is to design software architectures. Just as the name suggests, big data includes huge volumes of information.
To understand and process massive unstructured data, appropriate infrastructure is necessary. Big data engineers design and develop software systems that can efficiently store, process, and churn out useful information.
Conducts ETL Operations
Along with working to improve big data processing, ingestion, and storage, big data engineers also conduct extract transform load (ETL) operations. This essentially means collecting data from several different data lakes and consolidating it into a centralized storage location.
Doing the above allows different types of data to work together and provide useful information for business development. Big data engineers conduct ETL operations to allow data scientists and data analysts to have easier access to big data analytics.
Enforces Optimized Performance
The job of a big data engineer doesn’t just end at creating a platform. It also includes managing and revamping it. As a big data engineer, you are responsible for ensuring that the data infrastructure is performing at its highest capacity.
So, you use database optimization techniques that include data partitioning, data indexing, denormalization, and more for storage efficiency. You also undertake data mining to find format patterns to ensure efficient data ingestion for the database.
Big Data Engineer Education Pathways
Continue reading to discover the several educational pathways you can take to enter this profession. Choose the route that suits your financial, time, and career outlook preferences the most.
Big Data Engineer Degrees
The world of data engineering is an amalgamation of IT (information technology), data science, and engineering fields. The industry-standard education requirement is a bachelor’s degree, and you can get it in any of those fields.
Whether it’s a Bachelor’s Degree in Computer Science, Data Science, or Software Engineering, a bachelor’s is a great option. This degree path will take you approximately four to five years. Once paired with new skills, you will be ready for an entry-level job.
However, know that a bachelor’s degree isn’t your only university degree option. You can get a master’s degree in any of these fields to qualify for a higher level of big data engineering role. A master’s degree will take you two to three years, and a Master’s Degree in Data Science is most apt for this field.
For those looking to enter the world of research or post-secondary teaching, a Doctoral Degree in Big Data is the way to go. A PhD can take anywhere between four to five years, depending on your thesis and specialization.
Big Data Engineering Bootcamps
For those looking for a shorter educational pathway to become a big data engineer, coding bootcamps are the answer. A bootcamp can last anywhere between a couple of weeks to a few months.
The key to finding the best coding bootcamps lies in knowing your career goals, educational background, and finances. You can attend data engineering bootcamps such as Springboard, Flatiron School, and Fullstack Academy. We recommend attending bootcamps that offer a job guarantee and good career services.
Big Data Engineering Courses
Another way of learning big data engineering is via online courses. This educational pathway is ideal for everyone regardless of their tech background. You can enroll in beginner or advanced courses depending on your experience level.
Furthermore, you can learn various areas of this profession in a matter of just days to a couple of weeks. Make sure to enroll in courses that provide certificates so you can prove your qualification on your resume.
There are several popular massive open online course providers (MOOCs) that offer relevant data engineering courses. These include Udemy, LinkedIn Learning, Udacity, Coursera, edX, and plenty more.
How to Become a Big Data Engineer: A Step-by-Step Guide
Becoming a big data engineer requires more than just education. Read below to find out the different steps you can take to enter this profession. Know that the steps might vary from person to person, depending on your background.
Earn your degree
The first step to this career is to get the key educational qualifications. Employers typically hire bachelor degree holders, but you can also attend a coding bootcamp or enroll in online courses.
The next step is to gain a background in all the essential big data engineering fields. You should enroll in online courses that teach you data science and engineering to supplement your education.
The field of data science is in high demand, which makes competition for a job in the field significantly higher. In order to stand out, get additional certifications. There are several data science, professional engineering, and computer science certifications you can get.
Build your portfolio
Now that you have the educational background and additional certifications, add them to your professional portfolio. You can also apply for internships or do freelance work in the field to enhance your portfolio. Freelance websites Upwork and Fiverr offer data engineering jobs.
Apply for an entry-level big data engineering job
Once you complete the previous steps, you are ready for your first junior position. Apply for roles on job search websites such as Indeed.com, Glassdoor, or LinkedIn. If you have a degree, attend your university’s career fair to network.
Top Big Data Engineer Skills
These professionals are expected to possess a variety of tech and soft skills. To be an expert data engineer, you must have good teamwork skills along with tech skills.
Below are the primary tech skills that you need to become a big data engineer.
The field of big data engineering engages in software development and engineering. Thus, like many other data professions, you must have excellent programming skills. They include having ample experience with languages such as Python, C++, and Java.
Data Warehousing and Architecture
Having data skills is essential to this profession. So, in order to execute your responsibilities well, you need to know the data processes involved. They include constructing and knowing how to use a data warehouse, conducting ETL operations efficiently, and more.
You are also expected to have extensive experience with data mining and data modeling techniques. These techniques are used for efficient data storage, cleaning, and pattern recognition.
Hadoop and Apache Spark
You need to be proficient in big data platforms and frameworks to succeed in this profession. Hadoop is one of the most common tools used in this field. Thus, you must have an understanding of Hadoop-based analytics and technologies such as MapReduce, Hive, Apache Pig, and HDFS.
In addition to your Hadoop expertise, you must also have in-depth knowledge of the real-time processing frameworks. Apache Spark is one such popular framework, and you need to have good working knowledge. These are useful for managing and analyzing big data.
Big Data Engineer Salary and Job Outlook
By investing in learning big data engineering, you open yourself up to a career with a competitive salary and a promising future. According to ZipRecruiter, the national average salary of a big data engineer is a whopping $130,674 per year. You can earn up to $180,500 depending on your experience, place of work, and position.
In addition to a great salary, the profession is also in high demand. According to the Bureau of Labor Statistics, computer and information research scientist professions, which data engineering falls under, are projected to grow by 15 percent between 2019 to 2029. This means that there will be more job opportunities.
Entry-Level Big Data Engineer Job Requirements
The requirements for an entry-level position vary from company to company. The standard education requirement is a bachelor’s degree, but you can enter the field with online courses or a coding bootcamp certificate.
According to PayScale, the average salary for entry-level data engineers is $77,242 per year. Be aware that this figure will change depending on your education pathway and place of employment.
How to Prepare for Your Big Data Engineer Job Interview
To have a successful big data engineer job interview, you must be prepared. To do that, you need to go over your educational qualifications, essential skills, and project experiences. You should also practice common interview questions.
Keep reading to find the most common big data engineer job interview questions.
Big Data Engineer Job Interview Practice Questions
- What is your understanding of the term big data, and how does an engineer’s role fit into it?
- What is your experience with Hadoop technologies and other frameworks? Can you give us examples of projects where you have worked with these tools?
- What proficiency level do you have in programming languages such as Java, Python, and C++?
- What do you know about data engineering, structured data, and data warehousing?
- Why are you fit for this position, and what can you bring to the table that your competitors cannot?
Big Data Engineer Certifications
Having industry-relevant certifications can do wonders for your career because they validate your industry skills. This also applies to big data engineering.
However, know that there aren’t any mandatory professional certification requirements to qualify for the field. The certifications below are optional, and they can help you get a job in the field in some cases.
AWS Big Data Certification
The AWS (Amazon Web Services) Certified Big Data certification is great for any professional interested in this field. This certification is recommended for those who have at least two years of experience with AWS technology and a minimum of five years of hands-on experience in a data analytics field.
This certification will showcase your ability to implement data services with AWS, design and maintain big data infrastructure, and automate data analysis with machine learning. You can also use this certification if you want to become a data analyst or data architect.
Cloudera Certified Associate (CCA) Spark and Hadoop Developer
The CCA Spark and Hadoop Developer certification is fantastic for big data engineers because it covers the two essential big data tools. You are expected to know HDFS, ETL, Spark API, data analysis, and data loading to pass this certification exam.
There are no prerequisites for this CCA exam, and you are required to earn 70 percent or more to gain this certification.
IBM Certified Data Engineer - Big Data
For those interested in building a career as an IBM big data engineer, this certification is for you. To get this certification, you must have an understanding of many big data engineering elements. They include data modeling, network requirements, sources of data, latency, and many more.
How Long Does It Take to Become a Big Data Engineer?
The time it takes to become a big data engineer depends on your educational route. So, if you were to get a bachelor’s degree, it will take you around four to five years plus the time it takes to acquire other industry skills.
Additionally, if you choose to attend coding bootcamps, it takes a couple of months to learn big data engineering. However, this route requires you to prove your industry experience, so it will take you an additional year or two of in-field experience.
Why You Should Become a Big Data Engineer in 2021
If you love engineering, data infrastructure, and computer science and want a lucrative tech career, you should become a big data engineer. By choosing this career path, you secure a promising future and lucrative compensation package. There is no better time to become a big data engineer.
Big Data Engineer FAQ
To become a good big data engineer, you must have great data science, programming, Hadoop technology, and software engineering skills. Artificial intelligence and machine learning can also be helpful.
The most common programming languages used in big data engineering are Python, C++, and Java.
Yes, as data continues to become more and more relevant across industries, the demand for data professionals increases. This includes big data engineering professions.
The standard education requirement to become a big data engineer is a bachelor’s degree in a relevant field. The fields include computer science, engineering, and data science.