Data Infrastructure
Warehouses, ELT, reverse ETL, CDPs, and data modeling.
- Tools in the catalog
- 9
- Parser key
data_infrastructure, one of the eleven keys the scoring parser files tools under- Definition
- Glossary entry
What this function does
Data infrastructure copies data out of every tool into a warehouse, models it into tables people can trust, and pushes the results back into operational tools.
This is where a revenue stack gets an actual data model. Without it, each tool keeps its own version of the customer.
The tools
Listed alphabetically. Inclusion is not an endorsement or a rank.
- Airbyte
- BigQuery
- Census
- dbt
- Fivetran
- Hightouch
- Redshift
- Segment
- Snowflake
What job descriptions ask for
Postings ask for SQL, warehouse modeling, pipelines into and out of the CRM, and ownership of the data model itself.
How it shows up in the scores
A named warehouse or data model is the kind of integration evidence the Franken-Stack question looks for, so it can pull the score down. The work also pulls in the engineering skill category, which feeds Unicorn JD.
Every tool a posting names adds to its tool count, but the Franken-Stack score is not a tool count. It is a model judgment of how disconnected the stack is, with a written rationale. Read the bands or see how scored postings read today.
How often does Data Infrastructure appear in scored postings? The record counts tools per posting but does not yet store which category each tool falls in, so this page does not say, and does not rank the tools above.