Data engineer job opportunities will increase by 21% from 2018 to 2028. This staggering growth has many job seekers asking how to become a data engineer.
In this guide, we’ll define the role of a data engineer, detail the steps it takes to become one, and provide helpful tips to steer you in the right direction. Who knows? By the time you’re done reading, you may have chosen a new career path.
What is a data engineer?
A data engineer is responsible for managing the massive amounts of data companies collect. They design, build, and maintain the systems that collect, store, and process this data so it can be easily accessed and analyzed by data scientists and other specialists on their team.
What do data engineers do?
What a data engineer might do daily looks different from setting to setting and team to team. However, they’re typically responsible for the following general duties:
- Building data pipelines: Imagine a pipeline that takes raw data from various sources and transforms it into a clean, usable format. Data engineers design and build these pipelines to automate the flow of data.
- Managing data infrastructure: They’re responsible for setting up and maintaining the databases and data warehouses that store all this data. This ensures the data is secure, reliable, and accessible.
- Ensuring data quality: Inaccurate or incomplete data is not useful. Data engineers make sure data is clean and consistent by checking for errors and inconsistencies.
- Designing data architecture: Data engineers plan how to structure and organize data. This helps streamline how teams store, retrieve, and analyze data.
Data collection and management can be quite complex. Building data pipelines requires meticulous care to compile and organize data from many different sources.
Once an engineer is done compiling data (and building a data pipeline), they can use automation technology to keep the pipeline’s management running virtually on its own. Alerts can be set to warn data engineers of issues, outliers, or anomalies. However, it takes time, effort, and a heap of specified knowledge for data engineers to monitor and manage this process successfully.
Why become a data engineer?
We’ve already touched on data engineering’s growth projections over the coming years, but there are several other reasons why becoming a data engineer is a good choice. Compensation for data engineering roles is extremely competitive but can vary by company and industry.
Another attractive aspect that has many college grads wondering how to become a data engineer is the challenging and fulfilling nature of the work itself. The day-to-day tasks of a data engineer give potential applicants complex problems to sink their teeth into.
Additionally, a company’s data is among its most important assets. It has the power to help drive key decisions, streamline processes, and set the foundation for innovation. The prospect of making that sort of impact can be invigorating for prospective data engineers, as the work helps some of the world’s biggest companies thrive through data-driven decision-making.
Job seekers pursuing a career in data engineering will never have to worry about monotony. Because of the widespread use of data in today’s business world, potential data engineers can find a home in any number of industries, including finance, healthcare, and technology. Each day presents new problems to solve.
Skills required to become a data engineer
We know what a data engineer does and why you might want to become one, but what skills does the job require?
Successful data engineers possess technical skills and soft (intangible) skills. Prospective engineers should hone or learn the following in each category:
Technical skills:
- Programming: A strong foundation in programming is essential. Python is a popular choice for its readability and extensive data science libraries. Java and Scala are also widely used.
- Databases: Understanding relational databases (like MySQL and PostgreSQL) and NoSQL databases (like MongoDB and Cassandra) is crucial for storing and managing data.
- Big data technologies: To handle massive datasets, one must be familiar with big data frameworks like Hadoop, Apache Spark, and Apache Kafka.
- ETL tools: Data engineers build extract, transform, load (ETL) pipelines to move data between systems. Proficiency in ETL tools is essential.
- Cloud computing: Cloud platforms like Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) are widely used for data storage and processing. Familiarity with cloud concepts is a plus.
Soft skills:
- Problem-solving: Data engineers tackle complex challenges. Strong problem-solving skills are essential for designing and troubleshooting data pipelines.
- Communication: Effective communication with both technical and non-technical audiences is crucial for collaboration and explaining complex data concepts.
- Teamwork: Data engineering often involves collaboration with data scientists, analysts, and software engineers. Teamwork is essential for project success.
How long does it take to become a data engineer?
As you research these roles, you may also ask yourself, “How long does it take to become a data engineer?” The answer may vary since you can take two general paths to becoming one. You can pursue a traditional degree or explore alternate forms of education, like a certificate course.
If you go the traditional route, it can take four to five years to become a data engineer. This path requires a bachelor’s degree in computer science, IT, mathematics, or a related field. Students will also want to accumulate as much real-world experience through internships and other programs as possible during this time.
A quick internet search reveals a number of alternative education courses that show you how to become a data engineer without a degree. These courses can take much less time—weeks or months—as opposed to years. They are a perfect option for people with foundational knowledge, a related degree, or special circumstances preventing them from obtaining a traditional education.
The key with these classes is to choose a widely recognized, accredited course that won’t impede your chances of landing a job. It’s also worth noting that choosing the alternate education route may not always translate to an easy time landing a job.
How to become a data engineer: 6 steps
Becoming a data engineer is a great goal. But where do you start? The six steps below aim to give you the roadmap to launch your new career path.
1. Get data engineering education
First, decide on the education path that’s right for you. Ask yourself what type of data engineering position will meet your needs, and then work backward. Will that position require a formal four- or five-year education, or can you achieve your goals through an online certification course?
You can even find some online data engineering education options from accredited universities. For example, the University of Chicago offers an online data engineering course.
2. Grow your data engineering skills
To grow your skills, you’ll need to gain on-the-job experience in addition to your formal classroom education. Companies are looking for candidates with real-world experience in technical skills, including computer programming languages like Python, Java, SQL, R, and Scala. Knowledge of other technology concepts, like cloud computing, data warehousing, and machine learning, is also recommended. If you eventually want to learn how to become a big data engineer, even more skills may be necessary.
Seeking education in programming languages and technical skills can be easy enough. But what separates any job applicant from the rest of the pack is their soft skills.
Also take the time to master analytical, problem-solving, and communication skills. Data engineers don’t work in isolation. Most of the time, you’ll be working on big projects that require collaboration across multiple departments within your company. This means you’ll work with stakeholders outside the data world, like project managers or business analysts. Learning how to communicate effectively to help everyone get what they want from a project is priceless and will go a long way toward your future.
3. Build a portfolio
In today’s job market, you need to have more than skills on paper. A portfolio is a great way to showcase your skills and impact on driving tangible results.
However, it may be challenging to figure out where to start with your portfolio. The good news is that you don’t need a formal position to start building your body of work (e.g., data modeling projects, data pipelines, or code samples). Take a subject you’re interested in and create your own sample project around that. You can also freelance or offer your services on a volunteer basis to add to your portfolio of projects. Visit job board sites like Upwork, Freelancer, or Gun.io to research freelancing opportunities.
4. Consider an internship
An internship might be another possible avenue for on-the-job experience. Some of these positions offer compensation, and some don’t. Either way, you’re gaining the valuable experience you need to help you land a job as a data engineer.
Once you complete your formal education and have a handful of portfolio projects under your belt, start searching for one of these positions. Major job board sites, such as LinkedIn, Indeed, and Glassdoor advertise available positions.
5. Grow your network and find a mentor
Establishing a relationship with someone who is already succeeding in the field is a great way to streamline your data engineering journey. You can learn from their experience and ask questions, and they’ll likely give you personalized, one-on-one feedback.
Where do you find a mentor? Local conferences and meetups are a perfect starting point. Most industries have organizations built around creating a sense of community. Search local social media or meetup pages to find some in your area and get out there.
6. Search and apply for data engineering jobs
Finally, it’s time to search for and apply for data engineering jobs. It’s important to note that today’s job market is highly competitive across all industries. You’ll need to tailor each resume you submit to the position you’re applying for to stand out from the crowd.
And to really stand out, be sure to leverage your network and connections to get the inside scoop on any open roles at their companies. A referral from an existing employee is invaluable in a competitive job market.
A simple way to optimize your resume is to avoid mentioning any education or work experience that doesn’t relate to the job you’re applying for. Human resources professionals and recruiters don’t have the time to read through every single resume in a stack of thousands. As such, they use applicant tracking software (ATS) platforms to skim each resume and look for keywords related to the opening they wish to fill.
It also helps to showcase your portfolio of work on platforms like LinkedIn or a personal website to demonstrate your skills and so you can easily include a link to your work when applying for roles.
Check out data jobs at Intuit
Now that you know how to get a job as a data engineer, it’s time to begin your new career journey. Wherever you are on the engineering spectrum, there are tips in this guide that you can implement today.
One final tip we can offer is to see if Intuit has any data engineering positions available and learn about the skills we’re looking for in a data engineering candidate.