As I dive deeper into my first data/analytics engineering role, I’ve been wondering – what does ‘normal’ look like in this field? My current team’s process goes like this: we have a product manager who gathers business requirements from other PMs, writes the queries containing all the business logic, and then hands them over to our team of analytics engineers. We take those queries, clean them up, break them into components as needed, validate the output data against example cases, and then productionalize them into pipelines.
But here’s the thing – I’m not entirely sure if this is how it’s supposed to work. Do engineers typically not write the initial business logic themselves? How do other teams gather and translate business requirements? And how well do they really know their source tables and data models in day-to-day work?
For me, our sprint planning, reviews, and refinements sometimes feel more like formalities than productive sessions. I’m curious to know if others feel the same way. Does your process feel bureaucratic, or does it genuinely help produce better outcomes?
If you’re willing to share, I’d love to hear how your team approaches this and how involved engineers typically are in shaping the actual logic before production. It’s time to get a better grip on the data we work with.