The demand for Data Engineers recently rose around 45%, and with an average salary of about $111,000 or higher, a data engineering career comes with a lot of promise for job security. To position yourself for a top job as a Data Engineer, you’ll need to showcase the right skills and keywords on your resume.
Keep reading to learn how to build a Data Engineer resume, how to highlight your hard and soft skills, and the best keywords to include on your resume to grab the attention of employers.
What to include on your Data Engineer resume
Along with your skills, your resume should include things about you that help employers get in touch with you, understand what drives you, and what qualifies you for the position. Here’s the standard information to put on your resume.
Always include your name, address, email address, and phone number at the top of your resume. That way it’s easy for the hiring manager to locate it when they’re ready to reach out to you. Also, keep in mind that using an email address derived from your real name isn’t just professional, but also a nice way to build your personal brand.
While it’s not required, a brief declaration of what you’re looking to achieve helps the employer understand your sense of direction and what drove you to apply for the position.
Your objective statement can read something like this:
“Data Engineer looking for an entry-level position that allows me to implement natural language processing tools, as well as evaluate the workflow and increase the efficiency of data pipelines to help the organization accomplish its objectives.”
Your experience section should include:
- All jobs you’ve held that somehow prepared you for the tasks you’ll perform in the position.
- Real-world problems you’ve solved in past roles or courses
- Experience you’ve gained doing volunteer work involving database skills, including teaching at coding camps or a school-based program
Hard skills for your Data Engineer resume
Data Engineers design, build and maintain databases. To show you can deliver actionable database solutions, you’ll want to highlight your technical skills on your resume. This includes your proficiency with different programming languages and applications, such as:
Coding languages for your Data Engineer resume
- SQL: Structured Query Language (SQL) is used to program databases and manage how applications access the data in them. SQL is also used to analyze large volumes of data, including business data.
- Python: Python is a programming language used for many different types of applications, including web apps, operating systems, machine learning, and mobile apps. Because these applications often depend on databases, you’ll want to show that you’re proficient with Python.
- R: You use R to analyze data and develop software that presents data and recommendations in a way that makes it actionable for various stakeholders. (Check out our Analyze Data With R course to learn how.) It’s a programming language that’s central to the job of many data miners and statisticians.
Programs Data Engineers should show on their resumes
While showing your skill with the coding languages above, you’ll also want to showcase your ability to use the applications Data Engineers use on a daily basis. These include the following:
- Apache: Apache is a software library used to process large sets of data in a clustered environment. A clustered design ecosystem makes it easier to manage how applications access the various dependencies they need to run. With Apache, you can build tools for a relatively small number of users or a fairly simple set of operations, but you can scale it quickly.
Because many different people and departments use data sets, the scalability of Apache is a useful asset for businesses. Showing your Apache skills on your resume can let an employer know that you can create and work with scalable data solutions.
- Amazon Web Services and Redshift: Amazon Web Services is one of the leading platforms for designers, developers, and Database Engineers, and Redshift is a web services tool specifically made for warehousing data. A data warehouse refers to a database that applications and individuals can use to query and analyze data sets.
Because Amazon Web Services has become a go-to resource for many companies, showing you’re comfortable working with data in Redshift may make you an easy fit for a lot of businesses.
- ETL tools: ETL stands for extract, transfer, load, and it’s a general term describing how data gets used and applied. Data is extracted, transferred to a useable format, and then loaded to a data warehouse.
ETL tools work by applying rules to the data to leverage them for business insights. As a Data Engineer, you would play a role in designing the rules according to your employer’s needs and interpreting the results outputted by the ETL tools.
- C++: With C++, you can process as much as a full gig of data in one second. It’s often used to work with data sets when a predefined algorithm is not already manipulating them. C++ puts you, the Data Engineer, in the driver’s seat as you choose how to best analyze and present your data.
One of the main reasons you’ll want to show your C++ skills is because you can use them to perform predictive analysis. Predictive analysis is a key component of machine learning. Companies use it to help discover patterns and then predict what may happen given similar circumstances in the future.
If you highlight your C++ abilities, you may stand out as someone who’s comfortable working with big data, a useful ability in the modern business landscape.
Soft skills for a data engineer resume
In addition to these hard skills, you need the following soft skills to ensure your ideas are heard and you can work well with others.
- Communication skills: Because you’ll have to listen to, learn from, and interact with teammates, executives, and other stakeholders, you’ll need to show you have strong communication skills. One way to do this is to use keywords like “worked with,” “outlined,” “interfaced with,” and “collaborated with” on your resume.
- Presentation skills: A Data Engineer needs to turn numbers into compelling insights and then present them in a way that moves listeners to act, which requires presentation skills. Highlighting these on your resume can be easier if you use keywords pertaining to common presentation apps and tools. These may include PowerPoint, Google Slides, Canva, Beautiful.ai, and Genially.
As the demand for data engineering professionals continues to grow, many people are building rewarding and high-paying careers in this exciting field. And a polished resume that highlights the right skills and background can help you land an interview for your next Data Engineer role.
If you’re interested in learning a new programming language to support your career or add to your existing knowledge, check out our course catalog, including classes like Learn SQL, Learn Python, Learn R, and Learn C++. You can also work on strengthening your portfolio to support your resume with our portfolio projects. Get started today for free.