Ratio of data engineers to analytics engineers
18d ago in 🛠️ | Tooling
Ratio of data engineers to analytics engineers
What is the ratio of people in your organization who are working on your data integration layer vs your data modeling/transformation layer vs BI/Visualization layer?
Regardless of job title, be it data engineer, analytics engineer, data analyst, reporting analyst, whatever, how many people in your stack are working just on data integration vs modeling?
I ask because I've seen this fluctuate in the orgs I'm in based on tooling choice and the health of the system. In the best, most agile org, the ratio of data engineers to analytics engineers was 1:3 to 1:4.
In the least agile, most frustrating (for the business stakeholders waiting on data and reports), the ratio was 3:1 to 4:1, totally reversed.
Thus far, this has been a tooling issue. The choice of data integration tool caused an enormous amount of manual work to acquire data and put together all the orchestration pieces etc before it was available for modeling or transformation.
Help me fight my bias and tell me what you've seen in your previous roles and in your current role
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