ELT for SaaS and startups
Go from product databases and events to a warehouse layer without hiring a dedicated data team. Skippr Cloud ELT ingests, cleanses, and generates reviewable dbt.
See ELT product and Install.
The data problem
| Challenge | What you see |
|---|---|
| No dedicated data team | Engineers ship product; nobody owns pipelines or modeling full time. |
| Scattered product data | Postgres, events, and third-party tools each tell part of the story. |
| Manual board reporting | Leadership asks for cohorts and revenue; the answer is another CSV export. |
How Skippr Cloud ELT helps
- Stand up ingestion, cleansing, and modeled tables in one session. See Quick start.
- Generate bronze, silver, and gold dbt you can review. See Data modeling.
- Run the binary where the data already is. See Install.
Sources teams use
- PostgreSQL — hub: PostgreSQL
- MySQL — hub: MySQL
- MongoDB — hub: MongoDB
- S3 (event logs) — hub: S3
- Kafka — hub: Kafka
Warehouses
- BigQuery — hub: BigQuery
- Snowflake — hub: Snowflake
- MotherDuck — hub: MotherDuck
Trust
- Self-hosted runner: source data stays on the path you configure.
- Confirm SOC 2 and GDPR requirements with Contact for your deployment.