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

Jobs that work with vast amounts of data are in demand. Positions for data administrators and data architects, for example, are expected to increase by 9 percent from 2023 to 2033, which is much faster than the national average growth rate for all occupations, which is 4 percent during the same period, according to the US Bureau of Labor Statistics (BLS) [1]. The BLS states the rise in jobs is due to factors such as an increase in cloud computing and the adoption of artificial intelligence (AI), among other reasons.

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.

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 RapidMiner and KNIME.

• Machine learning: Feature your machine learning skills, including natural language processing, for big data applications specific to 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 AWS and IBM. You can also find certifications through organizations like Cloudera or Certified Analytics Professional.

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 BLS. A database administrator or architect, for example, typically need 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 [2], suggesting the possibility of other educational routes to enter the field. For example, you might opt to pursue an alternative credential to become career-ready, such as Google’s 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: $101,510 [3]

• Data scientist: $108,020 [4]

• Database architect: $134,700 [5]

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.

Key takeaways

• 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.

Earn credentials to add to your big data resume on Coursera

Learn more about big data to decide if a big data job is right for you or boost your current career path with more information from the field.

You can try the Microsoft Power BI Data Analyst Professional Certificate to cultivate a deeper understanding of tools like Power BI and how to create dynamic data visualizations. You can also learn about specific applications with the Machine Learning Specialization from Stanford and DeepLearning.AI, which covers machine learning, programming in Python, and more. You’ll find these options, among others, on Coursera.