Code-native, validation-friendly ingestion for regulated data. Built on dlt, run on dltHub.
Financial services teams building on dltHub
For financial services
dlt pipelines are code-native and version-controlled, and the dltHub context catalog carries the lineage. Mapped to SR 11-7, SOX ITGC, and BCBS 239.
Pin the validated baseline
git tag validated/market-feed@2.1.0tag created · this exact code is what auditors review
Prove it behaves the same every run
pytest tests/behavioural/187 passed · reproducible, deterministic output
Open the evidence trail
dlthub showrun history, schema contracts, lineage · your audit record
dlt consolidates data from core banking systems, market feeds, REST APIs, SQL databases, and files into Snowflake; dltHub runs it as managed infrastructure in your own environment. The 30-day POC ships with the evidence pack your Model Risk and SOX teams review, and Snowflake stays your orchestrator of record.
One regulated source into Snowflake, in your own environment, time-boxed to 30 days. For example one core-banking table, a market feed, or a risk dataset. The output is a reusable template, not a bespoke pilot.
The pipeline itself, ready for Model Risk and SOX review.
Generated by the run and mapped to SR 11-7, SOX ITGC, and BCBS 239.
Pipeline two to ten gets cheaper, not equally expensive.
SR 11-7 asks your model validation team for reproducibility and documentation. dlt pipelines are versioned code with deterministic behavioural tests, and the dltHub context catalog records lineage from source to model-ready data. Validation stays your process; dltHub produces the artefacts it reviews.
Change management runs through the controls your auditors already test: pull requests, CI gates, and releases pinned to a git tag. Every production run is traceable to the exact code version that produced it, with run history as the change record.
The dltHub context catalog records object-level lineage, schema contracts, and run state at every hop from source to RAW to model-ready. That gives risk aggregation reports a traceable path back to origin.
Your records stay in your storage: dlt loads into your Snowflake or warehouse, where your existing retention and WORM controls apply. dltHub adds the run history and lineage that document how each record was produced.
DORA applies to you as the financial entity; dltHub supports your ICT risk management with observability, alerting, and run history, plus a vendor-risk pack (SOC 2, architecture, data handling) for your third-party register.
Bring one source and one stakeholder from Model Risk or SOX. We map the validation package to your framework before any code runs.