DatriseAI-first ETL

Recruitee to Amazon QuickSight Integration

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

How Datrise loads Recruitee into Amazon QuickSight

Datrise syncs Recruitee's candidates, offers, jobs, interviews, pipeline stages, and evaluations into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Recruitee: Collaborative hiring and candidate pipelines.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Recruitee entities map to Amazon QuickSight

Recruitee entityAmazon QuickSight objectNotes
candidatesrecruitee_candidatesid PK · custom fields → flattened columns for analyses
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 Amazon QuickSight?

Flexible values are stored as flattened columns for analyses, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon QuickSight types.

How does the Recruitee to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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