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Principles of Data Wrangling by Connor Carreras, Sean Kandel, Jeffrey Heer, Tye Rattenbury, Joseph M. Hellerstein

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Chapter 8. Roles and Responsibilities

There are a number of common job titles and roles for people who work with data. In our experience, the most common are data engineer, data architect, data scientist, and analyst. In this chapter, we provide a general overview of each of these roles, which actions in the workflow they tend to be responsible for, and some best practices for managing the hand-off between these roles and for driving the long-term success of your data practices.

Skills and Responsibilities

We’ll provide a basic overview of the four common job roles that we encounter when working with data. Of course, in smaller organizations or in personal projects, a single person can end up developing and applying all of the skills and responsibilities that we’ll discuss. However, it’s more common to split them into separate job roles.

Our discussion is oriented on two axes (see Figure 8-1). The first axis is focused on the primary kind of output produced by someone in the role. The second axis is focused on the skills and methods utilized to produce that output. We’ll discuss each role in turn.

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Figure 8-1. Relative positions of the four key data wrangling user profiles based on output (internal or external) and skills (technically focused or business focused)

Data Engineer

Data engineers are responsible for the creation and upkeep of the systems that store, process, and move ...

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