ELT stands for Extract, Load, and Transform of data. ELT is a process whereby a system first extracts data from various sources and then loaded as-is into a data warehouse. Finally, the data is transformed directly in the data warehouse (normally using SQL) into a standardized format suitable for analysis/ML. Compared to the traditional ETL process, where data is transformed in an external engine, like Spark, before it is loaded into the warehouse, in ELT, the data is transformed in-place using SQL in the data warehouse.
ELT is often found in feature pipelines that extract data from existing data stores, load it into a data warehouse or feature store, and then transform the raw data into features in the data warehouse or feature store.