DatriseAI-first ETL

Workable to CSV Files Integration

AI-first ETL from Workable into CSV Files. Governed entities, incremental sync, typed landing tables.

How Datrise loads Workable into CSV Files

Datrise syncs Workable's candidates, jobs, applications, interviews, offers, and pipeline stages 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

Workable: Recruiting pipeline and candidate evaluation.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Workable entities map to CSV Files

Workable entityCSV Files objectNotes
candidatesworkable_candidatesid PK · custom fields → JSON-encoded strings for nested fields
jobsworkable_jobsid PK · linked to workable_candidates
applicationsworkable_applicationsid PK · linked to workable_candidates
interviewsworkable_interviewsid PK · linked to workable_candidates

FAQ

How does Datrise handle Workable'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 Workable 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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