Greenhouse to CSV Files Integration
AI-first ETL from Greenhouse into CSV Files. Governed entities, incremental sync, typed landing tables.
How Datrise loads Greenhouse into CSV Files
Datrise syncs Greenhouse's candidates, applications, jobs, interviews, scorecards, and offers into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.
Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.
Ideal for portable hand-off into any tool that ingests delimited files.
Endpoints
Greenhouse: Applicant tracking and structured hiring.
CSV Files: Flat-file destination for exports and lightweight data sharing.
How Greenhouse entities map to CSV Files
| Greenhouse entity | CSV Files object | Notes |
|---|---|---|
| candidates | greenhouse_candidates | id PK · custom fields → JSON-encoded strings for nested fields |
| applications | greenhouse_applications | id PK · linked to greenhouse_candidates |
| jobs | greenhouse_jobs | id PK · linked to greenhouse_candidates |
| interviews | greenhouse_interviews | id PK · linked to greenhouse_candidates |
FAQ
How does Datrise handle Greenhouse's custom fields in CSV Files?
Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.
How does the Greenhouse to CSV Files sync stay up to date?
It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.
Related pipelines
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