Analytics Engineer

The journey

1. What you learn

   1. Raw data transformed into models an organisation can trust
   2. Software engineering practice applied to analytics work
   3. Definitions owned centrally so numbers stop disagreeing
   4. Data quality tested rather than assumed

2. What you will understand

   1. The modelled layer as a product with real consumers
   2. One metric definition, owned in one place, used everywhere
   3. Tests on data as well as on the code that transforms it
   4. Why two dashboards disagree, and whose job it is to fix that

3. What you will build

   1. A tested, documented modelled layer that analysts build on without you
   2. A metric definition set that resolves a real disagreement between two teams
4. 1. The proof you build

      Evidence that you can build a data layer an organisation trusts enough to make decisions on.

      See how proof works