Computing with data is at the heart of the statistical office. Yet, the area of technical computing often falls between the two stools of data analysts and IT developers. In this presentation I demonstrate the importance of various computational skills across the Generic Statistical Business Process model. As we will see, many of the skills are as specific to working with data as they are uncommon to typical IT development teams. However, I argue that there is also a common ground between the worlds of Computing with Data and IT development. This is the field of Software Engineering: the range of techniques and methods aimed at ensuring that software meets quality standards, including maintainability, usability, performance, and so on. I argue that Statistical Offices have a natural need for the role of ‘Research Software Engineer’ (RSE): a person who develops software, based on an understanding of the research goals. An RSE combines an understanding of data processing goals, methods, and technologies while being competent in software engineering, thereby filling the gap between the typical competence areas of statistical analysts and IT developers.
