This is a new role. Today our data scientists check data quality and availability while also building models. We are creating this position so the data layer has a dedicated owner and issues are caught early, before they affect decisions.

Own the inventory of every credit data source, including TransUnion, Clarity, Plaid, Prism, and internal data from the app and loan servicing.

Define, for each source, what data Credit Risk needs, at what grain, how fresh it must be, and where it lands.

Write data contracts with the engineers who build the vendor integrations, covering expected fields, types, null rules, and volumes.

Confirm that raw vendor responses are stored completely and can be reused for model development and audits.

Monitor freshness, volume, fill rate, and schema for every source and every model input.

Set up alerts for when a feature's fill rate drops, a vendor stops returning a field, or volumes deviate from baseline.

Track input drift for production models alongside the data scientists.

Triage data incidents: find the root cause, route the fix to the right owner, and track it to closure.

Own the Credit Risk layer of our Snowflake warehouse, including raw, staging, mart, and feature tables.

Build and maintain the pipelines and transformations behind application, loan, performance, and vendor data.

Keep modeling datasets reproducible, so data scientists can rebuild a point-in-time training set without leakage.

Credit Risk Data Engineer

Responsibilities

Qualification

Required

Preferred

Company

Kiwi

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