The role between engineering and analysis.
WHAT IT IS
Transforming raw data into modelled, tested, documented datasets that analysts and tools consume.
WHERE IT SITS
Between data engineering, which moves data, and analysis, which interprets it.
WHY THE ROLE EMERGED
Warehouses became powerful enough that transformation moved into SQL, which analysts could write.
WHAT IT REQUIRES
Strong SQL Data modelling
Software engineering practice: version control, testing, review
Understanding of the business
WHY THAT LAST POINT MATTERS MOST
The work is encoding business definitions, and getting them wrong is invisible until someone acts on a wrong number.
WHAT THE OUTPUT IS
Tables that mean what their names say, tested and documented.
WHAT DISTINGUISHES IT FROM ANALYSIS
Analysts answer questions. Analytics engineers build the foundation they answer from.
WHAT DISTINGUISHES IT FROM DATA ENGINEERING
Less infrastructure, more modelling and definition.
WHAT THE MEASURE OF SUCCESS IS
Analysts not needing to ask what a column means, or whether a number is right.
WHAT TO BUILD
Models that are obvious, tested, and owned.
