I started this blog in 2015 to serve as reference material for Choroplethr, my open source R package for mapping demographic statistics. A lot has changed since then, and I’ve decided to start using this space for something else: to codify my thoughts on the new field of Analytics Engineering.
As a software engineer, there is probably no greater feeling than creating your own open source project and seeing it grow in popularity. That feeling led me to dedicate my nights and weekends to Choroplethr, even when I had a full time job as a software engineer at a tech company.
That effort paid off. After becoming self-employed I wound up getting consulting contracts directly related to Choroplethr. It also led to contracts to deliver introductory R training, which was a new and enjoyable type of work for me.
The only downside to this work is that it is incredibly niche. At some point I started to miss aspects of my old job: being a part of a team, being exposed to new technologies, and feeling that my work was part of a larger whole. By contrast, as a consultant my involvement with an organization was typically limited to a specific type of expertise I could bring them at a specific time that they needed it.
As a result, last year I began looking for contracts that were more broadly in the space of software engineering and data analysis. I no longer had a requirement that the work be related to Choroplethr or training. A former training client wound up hiring me to help them build a data pipeline and maintain their internal library of R packages. This project took six months and just ended. I enjoyed it so much that I have decided to start looking for similar work.
The first step in finding similar work is being able to name what you’re looking for. Perhaps this is an artifact of the Google age, where all searches seem to be based on keywords. The closest job title to what I did with this client seems to be Analytics Engineer.
All job titles are a bit fuzzy, and I believe that Analytics Engineer is not different than, for example, “Data Scientist” in that respect. In the coming weeks and months I hope to use this space to codify what I think this role means, and how I see it fitting into modern data organizations.