The days of hiring a single data scientist to determine your data analytics strategy are long gone. As the impact of big data analytics expands across the business, so do the roles that support this increasingly strategic function. This talent transformation is evident with newly minted roles in the C-Suite, such as the Chief Data Officer and Chief Digital Officer, and more specialized positions emerging in departments including Marketing, Finance, and Human Resources.

Below we share some of the latest views on established data analytics roles, as well as some new ones, as highlighted in a recent Harvard Business Review (HBR) article on how to build your data analytics dream team. Take a look:

  • Data Engineers: According to the HBR article, data engineers play a key operational role in your data analytics team. This includes overseeing data collection and data management, as well as data storage. The work of data engineers is the “foundation of a data operation” and focuses on the maintenance and preparation of data for use by other parts of the company, according to the article.
  • Data Scientists: A more commonly known data analytics role, the data scientist determines how the company will use data, leveraging technologies like artificial intelligence (AI) and machine learning to generate business insights and make smarter decisions. According to HBR, the combination of data engineers and data scientists should form the “starting point” for companies seeking to develop a big data analytics strategy.
  • Data Translators: According to the HBR article, several new roles are emerging alongside the more established roles of data scientists and data engineers. The data translator role—also known as the data curator or the data storyteller—is a newer position that focuses on better connecting data analytics initiatives with the business. This includes helping turn insights into clear actions, engaging and training employees, and communicating big data analytics “needs and results” throughout the organization, including the C-Suite. 
  • Knowledge Engineers: Another newer role is that of the knowledge engineer, also known as ontologists. They help companies understand how their data relates to the rest of the world. According to the HBR article, “Knowledge engineers build intelligence into computer systems—they create brains, of a sort, that can mimic human decisions.” As a result, knowledge engineers often have strength in a specific skill set, such as expertise in AI and machine learning.

If you’d like to learn more, including determining who’s going to lead your analytics dream team, check out the complete HBR article.