Big Data Developers


Education and Training Requirements

High School

You’ll need at least an associate's degree to work in big data, so it’s a good idea to take a college preparatory curriculum in high school. Take as many computer science classes—data analytics, database management, computer programming, computer security, and software development—as possible. Algebra, calculus, linear algebra, discrete mathematics, applied mathematics, and statistics classes will help you to build your math, analytical, and critical-thinking skills. Other helpful courses include English and speech (because you’ll need to be able to communicate effectively orally and in writing), a foreign language (especially if you plan to work outside the United States), art/design (so that you can present your findings visually), and psychology (to better understand how people think). If you plan to launch your own business, you should take business, marketing, and accounting classes.

Postsecondary Education

Your major and the level of education that you will need varies based on your chosen career. For example, data processing technicians must have a minimum of an associate’s degree in data science, database management, statistics, or a related field. Data warehousing specialists need at least a bachelor’s degree in database management, data science, management information systems, computer science, or another computer-related field. Data engineers and scientists must have a minimum of a master’s degree in data science, data analytics, computer science, artificial intelligence, mathematics, intelligent systems engineering, software engineering, or statistics. Others have degrees in economics, business, econometrics, computational psychology, operations research, or neuroscience. At some companies, engineers and scientists may be required to have a doctorate in one of the aforementioned fields.

Data analytics and science probably do not come to mind when you hear the word “apprenticeship,” but a growing number of tech companies, government agencies, and nonprofit organizations offer apprenticeships in data science and related fields. For example, IBM has a Data Science Apprenticeship Program that allows apprentices to work in artificial intelligence, cloud computing, artificial intelligence, cognitive software, and other areas. Visit to learn more about IT careers that can be entered through an apprenticeship.

Training in data science/analytics, engineering, and computer science is also offered in the armed forces. Visit for more information.  


Many colleges and universities offer certificates in data science, data analytics, and related fields. For example, Cornell University offers a certificate in data analytics to students who complete the following classes: Understanding and Visualizing Data, Implementing Scientific Decision Making, and Using Predictive Data Analysis. Earning a certificate is a great way to receive an introduction to the field and to build specialized skills that can help you to perform better at your job—and even get a promotion. Contact schools in your area to learn more about available programs. 

Other Education or Training

The fields of data science and data analytics are constantly changing due to the growing use of artificial intelligence, new software tools, increasing computing power, and advances in data collection and analysis techniques. As a result, big data developers must continue to learn throughout their careers in order to stay competitive on the job. Continuing education opportunities are provided by associations, for-profit and nonprofit schools (such as Coursera, edX, Global Knowledge Training LLC, and Udacity), and information technology (IT) companies such as IBM. For example, the Association for Computing Machinery offers more than 1,000 online courses on topics such as Big Data, data mining, data visualization, data warehousing, database design, business intelligence, data management, and business skills. The International Web Association provides a variety of classes including Intro to Programming Concepts, Introduction to C#, and Introduction to JavaScript. The IEEE Computer Society, International Web Association American Mathematical Society, American Statistical Society, INFORMS, and DAMA International also offer continuing education opportunities. Contact these organizations for more information.

Certification, Licensing, and Special Requirements

Certification or Licensing

TDWI, a membership association for data science professionals, provides the certified business intelligence professional credential to applicants who have a bachelor’s or master’s degree in information systems, computer science, accounting, business administration, engineering, mathematics, sciences, or statistics; have two or more years of full-time experience in computer information systems, data modeling, data planning, data definitions, metadata systems development, enterprise resource planning, systems analysis, application development and programming, or IT management; and pass examinations.

Certification credentials are also offered by the Institute for Certification of Computing Professionals (certified big data professional, business data management professional, and certified data scientist), DAMA International (certified data management professional), and INFORMS (associate certified analytics professional, certified analytics professional). Contact these organizations for more information.  

Experience, Skills, and Personality Traits

Those seeking entry-level positions typically obtain experience via internships or co-ops. For higher-level jobs, several years of experience in lower-level positions are required.  

Successful big data developers have a combination of technical and soft skills. Key technical skills include knowledge of programming languages; knowledge of machine learning techniques and algorithms; experience with NoSQL databases; expertise in data analysis, data mining, and data modeling; proficiency in using query languages; familiarity with cloud computing infrastructure; experience with data visualization tools; and experience with common data science toolkits.

Important soft skills for developers include the ability to communicate effectively orally and in writing, top-notch analytical and problem-solving ability, curiosity, the ability to work under tight deadlines, a detail oriented personality, good time management skills, and self-motivation and the ability to work independently, when needed. Aspiring managers should possess the aforementioned traits, as well as have strong leadership and business management skills.