Stop writing dbt boilerplate by hand — generate a complete staging layer, test YAML and mart skeleton from any schema input in seconds.
Paste a schema, CSV headers, sample JSON or an existing SQL query — get production-ready dbt staging models, schema YAML with tests and an optional mart layer, dialect-aware for BigQuery, Snowflake, Postgres and DuckDB.
Same URLs members use. After sign-in, free accounts see monthly limits where they apply; Premium unlocks full depth.
Every card is something members actually do inside Datamata — not a vague promise.
Staging CTAs, source() macros, renamed PKs and typed casts — the twenty minutes you skip every new table.
unique and not_null on primary keys, column descriptions in schema.yml — not something you add later.
Built for Premium outcomes
Real decisions, not generic templates. Every workflow runs on live market data so your moves are backed by what employers are asking for now.
Staging model with {{ source() }} macro, renamed PKs, dialect-aware type casts and a clean CTE pattern
schema.yml with source definition, column descriptions and not_null/unique tests wired to your PK
Optional fact or dimension mart model using {{ ref() }} pointing at the generated staging model
Datamata Premium
Full depth across tools, higher limits where they apply and a single member hub tied to the same live posting engine.
Get Datamata PremiumCancel anytime · Plans shown in billing
In action
Staging CTAs, source() macros, renamed PKs and typed casts — the twenty minutes you skip every new table.
Try dbt ModelsDDL, CSV headers, a JSON API response or an existing SELECT — the generator handles all four starting points.
Staging model with {{ source() }} macro, renamed PKs, dialect-aware type casts and a clean CTE pattern
Go deeper
unique and not_null on primary keys, column descriptions in schema.yml — not something you add later.
Browse all premium toolsSalary, skills, employers and the Match Engine all read the same live posting feed — so you are not comparing a benchmark from 2022 against jobs from this week.
Illustrative output — your generated models reflect the schema you paste and the dialect you pick.