The 3 Roles Needed for the Modern Data Team Posted on : Aug 19 - 2017

According to the McKinsey Global Institute, data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result. As more companies are working to reap the benefits of becoming data-driven, the demand for effective data teams becomes more prominent. But while some companies’ data teams run like well-oiled machines, the majority of enterprise organizations are still figuring out how to get their data teams up and running.

One of the most common mistakes is not properly defining and differentiating the roles and responsibilities of data team members. Let’s take a look at how you can create the foundation for a data-driven culture — starting with your core team.

Defining the Roles

At the core of your team should be a data engineer, data analyst and data scientist. Early on you might have one person filling more than one of these roles. While the titles sound similar — and many job listings contribute to this ambiguity — there are some important distinctions between each:

Data engineer:  Your data engineer — sometimes called an ETL (extract, transform, load) engineer —  is responsible for moving and propagating access to data. Rather than analyze and interpret the data, their chief mandate is piping it to the right places.

Data analyst: Your data analyst should be focused on answering business questions using data. They know SQL and may be comfortable in a few other languages such as Python or R. This person effectively serves as the bridge between data and business insights. Generally, this is a person holds an advanced math or physics degree and exhibits an abnormal amount of intellectual curiosity and skepticism.

Data scientist: Oh, the data scientist. Much like big data, data science is the buzzword of the decade. While the term is often misused — companies often mistakenly cite the need for a data scientist when what they’re really looking for is an analyst — this role has a specific purpose: Their job is to build predictive models and automated classifications off of your existing data to help guide future decisions and predict outcomes. This person should have a proficient background in statistics and some coding chops to get those math functions implemented in their analytics. View More