How to Write a Big Data Resume (Step-by-Step with Examples)

Key takeaways

Feature your professional experience and skills in programming, machine learning, and natural language processing in your big data resume.

• Your resume summary can emphasize your experience working with big data and data analysis, and list the industries you’ve worked in.

• Find relevant keywords in the big data job description and incorporate them into your resume.

• You can use your big data resume to apply for roles such as data scientist, database administrator, and database architect.

Learn more about how to create a big data resume, and explore potential career paths in the field. If you’re ready to develop your skills, consider enrolling in the DeepLearning.AI Data Analytics Professional Certificate. In as little as four months, you’ll have the opportunity to learn about data visualization, storytelling, and generative AI for analytics. Upon completion, you’ll have earned a shareable certificate for your resume and LinkedIn profile.

What do employers look for in a big data resume?

Your resume should reflect your work in big data or your interest in beginning a career in the field to give hiring managers and potential employers an idea of your experience, education, skills, and other factors that can help you land a job there.

Your resume for a big data job could include skills in programming languages like Python and Java, machine learning, natural language processing (NLP), and data mining, among others.

Learn more about how you can leverage these skills in a concise and visually appealing way on a resume to get a position in the field of big data.

Step 1: Create a big data resume template.

First, you must decide the manner in which you want to present your information on your resume. Three options you can choose from for a resume template are:

• Chronological format: A chronological resume starts with your most recent professional experience and works backward to older experience to showcase what you’ve accomplished in previous positions. This option is a good choice if you have previous work experience, and many employers prefer seeing this option.

• Functional format: Use a functional resume to showcase your skills with big data. If you don’t have previous experience, consider this option, as it highlights skills you may have picked up through your education.

• Combination format: Combine the best of a chronological and functional resume by showing the skills you used in previous big data positions. However, a combination resume can get lengthy, and potential employers prefer two pages or less.

Read more: Types of Resumes: Choosing the Right Format for Your Needs

Step 2: Fill in your basic big data resume essentials.

Your resume should include a way for potential employers to reach you, so it’s important to include your contact information prominently. Add your name, email address, phone number, and city and state of residence if potential big data positions are location-dependent.

It’s also a good idea to include a link to a website or online portfolio if you have one that can showcase your big data projects or previous work.

Step 3: Add your resume summary.

A resume summary should give prospective employers a brief look at your background and the skills and abilities that qualify you for the big data position you’re applying for.

Open by emphasizing your experience working with big data, data analysis, and other relevant technologies. Include any in-demand tools and skills you’re familiar with and certifications you’ve earned. Also, include a short overview of your previous experience, such as the industries or fields in which you’ve worked. If you’re new to the field, you can focus on your education or positions you’re interested in.

Step 4: Showcase your big data skills.

Employers are looking for specific skills for various positions in the field of big data. Some skills you could highlight on your resume include:

• Programming languages: Emphasize your proficiency in programming and cloud languages such as Python, Java, Go, C++, and Ruby.

• Data mining: Highlight your understanding of data mining tools, including software like Altair RapidMiner and KNIME.

• Machine learning: Feature your machine learning skills, including natural language processing, for big data applications specific to artificial intelligence (AI).

• Data visualization: Include your skills in processing data into a graphical representation, such as charts, maps, graphs, and other visuals.

It’s also important to show your workplace skills, which could include problem-solving, creativity, and adaptability, all of which can help you navigate big data positions successfully.

Step 5: Include your professional experience.

Your professional experience gives potential employers a good idea of your work and the skills you bring to a new position.

Start each work experience with the name of the company, the dates you worked there, and the titles you held. Then, add key points from your experience there, such as professional accomplishments, responsibilities, and skills acquired.

This section could also be a good spot to add keywords to your descriptions to help you stand out and showcase your ability to work with data and use it to derive critical insights. Review the job listing, and see if the descriptions of your professional experience include keywords that match or find ways to add them. 

Step 6: Feature your certifications.

Certifications show potential employers that you’re continuing to learn about the big data field or that you’re proficient in specific big data topics that can be relevant to a job.

You can choose from various certifications depending on what suits your particular skill set or what subjects you want to learn. Consider certifications from providers such as Amazon Web Services (AWS) and IBM. You can also find certifications through organizations like Cloudera or the Institute for Operations Research and Management Sciences (INFORMS). 

Step 7: Include your education.

Your education is important, especially if you are a recent graduate or entering the field of big data. You’ll need to add the name of your school along with your degree and field of study. 

Positions in data science and analysis usually need a bachelor’s degree, with employers preferring a master’s degree for some jobs, according to the US Bureau of Labor Statistics (BLS). A database administrator or architect, for example, typically needs a bachelor’s degree in computer or information technology. However, a data scientist should have a bachelor’s degree and may need a master’s or doctoral degree in mathematics, statistics, computer science, or a related field. 

According to research, 65 percent of big data analysts, for example, have a bachelor's and 15 percent have a master's, suggesting the possibility of other educational routes to enter the field [1]. For example, you might opt to pursue an alternative credential to become career-ready, such as the Google Data Analytics Professional Certificate or the IBM Machine Learning Professional Certificate.

Jobs with big data experience

You can find various positions that rely on big data skills, so it’s important to consider different options or find jobs that appeal to your specific skill set. Some positions that utilize big data skills and their median annual salary, based on data from the BLS, include:

• Database administrator: $104,620 [2]

• Data scientist: $112,590 [3]

• Database architect: $135,980 [2]

The states that employ the highest number of database administrators and architects are California, Texas, and Virginia, while California, Texas, and New York have the most data scientists [4].

Big data resume tips

• Choose a resume template that highlights your skills.

• Focus on information such as your experience, education, skills, certificates, and other relevant topics, mentioning specific projects and results when possible.

• Go through the job description to find relevant keywords that match your background and highlight them throughout your document.

• Make sure your resume is limited to two pages with the most important information included.

Explore big data resources for your career

Discover career tips and research industry trends by subscribing to our LinkedIn newsletter, Career Chat. Then, check out the following resources to learn more about a career in big data:

• Build your knowledge: Data Science Terminology and Definitions 

• Read an insider story: Meet the Data Analyst Using His Creativity to Tell Visual Stories 

• Consider your path: Data Analysis: Where to Start and How to Build This High-Income Skill 

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