It’s no overstatement that the world today runs on data: from social media to technology to finance. Even health is now presented as a series of measurables. This creates a near-endless need for the collection, storage, and analysis of large amounts of data – making the career of a data engineer an indispensable one nowadays.
You’ve probably heard about the vast opportunities for a data engineer, not to mention the high-salary careers that come with it. If you’re looking to jump into the rapidly-growing industry, here are four things you should consider when starting a career as a data engineer:
1. Choosing a Career Path
Being a data engineer is a vague answer in itself, as it has multiple career paths you can choose from. Each option has its own strengths and weaknesses, its own skill requirements, and its own challenges. Choosing a specific career option early on will give you a direction as well as a target once you start your career as a data engineer. You can be a big data engineer, a data architect, a business intelligence analyst, or more.
There’s no shortcut to identifying what career option suits you. You’ll have to do your research to understand what each one does and where each path leads. For example, a data architect is a critical role that analyzes business problems and requirements. From here, they form technology requirements that will form the backbone of the data structure, including the standards and principles that will guide them.
Meanwhile, big data engineers also vary in their jobs: there are those focused on the design and construction of data processing systems, there are those brought in for testing and benchmarking, and others are for maintenance. Additionally, there are positions that will let you experience all these stages of developing and running systems that handle large data sets.
2. Hard Skills: Mathematics and Programming
Mathematics and programming are basically the lifelines of becoming a data engineer. Of course, there are people naturally talented in these fields while there are people who got good through experience and hard work. The first question you should ask yourself is whether you’re ready to jump in knowing that these two are vital to the field. To clear things up, it doesn’t mean that you have to be good at math or have a solid foundation in programming to start. These skills can be learned, and if you have the mindset, you can grasp both in time.
It is important to know that data science – the field where data scientists and data engineers thrive – is math-oriented. However, as a data engineer, math will help you better understand the ideas behind most of the tools and solutions you will use. Once you’re in the field, you’ll most likely focus on the technical side of things, building data pipelines and preparing the interfaces needed to present these huge amounts of data.
As you build these technical requirements, you will need programming skills. The common advice for people starting as a data engineer is to learn how to write programs using Python, Java, or Scala. Although it depends on the work you’ll be looking for, these three languages are among the most commonly used: Python for modeling and statistical data analysis, Java for data architecture frameworks, and Scala for customized applications requiring Java interoperability.
3. Soft Skills To Thrive As a Data Engineer
Contrary to what you might see in pop culture, a data engineer regularly works with other people and frequently collaborates at different stages of a project. There are soft skills you should have and develop if you’re looking to be an effective data engineer.
To start, communication skills will get you through. You’ll have to work with people in charge of machine learning, data analytics engineering, developers, and other business units as needed. You might be brought in to provide updates from a data engineering standpoint, or even be tasked with explaining the issues that you’re currently trying to address.
Good communication skills show not only your knowledge of the subject at hand but also create a connection between you and the people you’re working with. Being able to articulate yourself well also ensures that you can relay any issues at hand, giving your collaborators enough understanding and ample time to respond.
Organizational skills are also important if you plan to start a career as a data engineer, which also applies to everyone working with big data. Getting a good handle on all aspects of your work, plus the ability to immediately recover a file or any information as needed will save you valuable time.
4. Degrees and Certifications
Working in a fast-changing environment, professionals in the big data industry are required to continuously learn and improve themselves. If you’re planning ahead for a career as a data engineer, you’ll have an advantage if you’ll take a bachelor’s degree relevant to the field. Usually, big data companies require degrees in data science, computer science, mathematics, finance, or management. Degrees in psychology, engineering, and information technology (IT) are also welcome.
Once you start working, certifications become stepping stones for you to rise on the career ladder. Most companies host their own organization trainings to share new skills and knowledge with their employees, or to build a stronger company culture. Depending on your position and the organization that you’ll be joining, others require certain professional data engineer certifications such as those coming from Google or IBM or even ask you to complete a security awareness training.
Planning ahead of time will help you launch a more focused and guided career as a data engineer. There’s a lot of opportunities for growth and development in the data science and engineering industry; find one that suits you and make the most out of it.