DatriseAI-first ETL

Recruitee to Looker Integration

AI-first ETL from Recruitee into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Recruitee into Looker

Datrise syncs Recruitee's candidates, offers, jobs, interviews, pipeline stages, and evaluations into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

Recruitee: Collaborative hiring and candidate pipelines.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Recruitee entities map to Looker

Recruitee entityLooker objectNotes
candidatesrecruitee_candidatesid PK · custom fields → flattened columns (nested fields expanded for modeling)
offersrecruitee_offersid PK · linked to recruitee_candidates
jobsrecruitee_jobsid PK · linked to recruitee_candidates
interviewsrecruitee_interviewsid PK · linked to recruitee_candidates

FAQ

How does Datrise handle Recruitee's custom fields in Looker?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the Recruitee to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

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