At DFP, we often introduce ourselves to new team members by mentioning an interesting fact that perhaps not everyone knows. So, it came to be that I mentioned becoming a beekeeper.
Currently, beekeeping is not my main job, as at DFP I head up data engineering. This places me right in the middle of data science and the applications/devops team. Data engineering is a great space to be in at the moment, since these days every company is a data company.
So, do the worlds of beekeeping and data engineering align?
On the face of it, not at all. This can best be highlighted by the adage ‘Get two beekeepers in a room and you’ll have at least three opinions.’ Whereas with data engineering there’s always one correct/proper way. Sure, there are many approaches to a job, and even more tools to use, but once you hit that sweet spot, it’s obvious. Get the architecture right, and away you go.
However, you can draw some parallels. There are three main types of bees in a honey hive: Worker, Drone and Queen. It’s perhaps most applicable to correlate the activities of a data engineer with those of the Worker bee. They both:
- Are responsible for building the right environment
- Clear out debris and reinforce/build-on, where necessary
- Forage for data to feed the hive.
Worker bees (data engineers) as pollinators are extremely valuable in terms of their contribution to the hive (business) but also the wider environment (economy). That being said, all bees are essential – Why is it important to save the bees?
Bees are incredibly disciplined, with clear lines of responsibility. A hive that is down on numbers for key roles will struggle – and excess numbers in any particular area can cause problems, too. It’s all about balance.
Likewise, this is true for a data-centric organisation. Lines of responsibility and the balance of the team is critical to producing high-quality results, as well as for respecting and valuing the strengths of each team member.
Also, a start-up hive (organization) isn’t quite as polished or well-structured as it could be, but with commitment great results will ensue. Which is when you can sit back and start enjoying the honey.
And for the record, I’m not the first data engineer to have a love of all things bee.