Python
transformation
Python for data engineering
Custom transformations, glue, and anywhere-code.
Python is the glue of every real data stack. Custom connectors, transformations that dbt can't express, ML pipelines, and the bash-script replacement layer. We write Python that's boring in the best way: tested, packaged, deployed, and owned.
Python · live signal
What we've shipped with Python
0+
custom modules shipped
0%
typed + tested
0+
custom connectors
When Python makes sense
Pick Python when…
- You need a custom connector no vendor offers
- Transformations need real logic (not just SQL)
- You want typed, tested, reviewable data code
- ML or scoring pipelines live alongside analytics
What we implement
Beyond the tutorial.
01
Custom connectors
Typed API clients with retries, pagination, and backfill.
02
Transformation modules
Pydantic-validated, tested modules used from dbt/Airflow/Dagster.
03
ML pipelines
Train/score loops with reproducibility, tracking, and deployment.
04
Package + deploy
Poetry / uv packaging, CI, and production rollout.
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