DatriseAI-first ETL

Recruitee Databricks SQL Warehouse

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

How Datrise loads Recruitee into Databricks SQL Warehouse

Datrise syncs Recruitee's records, events, and configuration objects into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Recruitee: SaaS or API data source for analytics and warehouse sync.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Recruitee entities map to Databricks SQL Warehouse

Recruitee entityDatabricks SQL Warehouse objectNotes
recordsrecruitee_recordsid PK · custom fields → VARIANT or STRUCT columns
eventsrecruitee_eventsTIMESTAMP events
configuration objectsrecruitee_configuration_objectsid PK · linked to recruitee_records

FAQ

How does Datrise handle Recruitee's custom fields in Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Recruitee to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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