Credit Risk Data Engineer

About the role

We are seeking a Data Engineer to own the data layer that powers Kiwi's credit risk decisions. You will ensure that Credit Risk always has the right data, at the right time, in the right shape, and that any data issues are detected and resolved before they impact underwriting or renewal decisions.

Key responsibilities

• Maintain an inventory of all credit data sources (TransUnion, Clarity, Plaid, Prism, internal app and loan‑servicing data) and define data needs, granularity, freshness and landing locations.
• Write data contracts with integration engineers, store raw vendor responses, and monitor freshness, volume, fill‑rate and schema for each source.
• Set up alerts for feature fill‑rate drops, missing vendor fields or volume deviations, and track input drift for production models.
• Tri­age data incidents, identify root causes, route fixes and ensure closure.
• Own the Credit Risk layer in Snowflake (raw, staging, mart, feature tables) and build pipelines for application, loan, performance and vendor data.
• Maintain reproducible modeling datasets, write automated data‑quality tests, and keep documentation and lineage up to date.
• Support vendor oversight by checking SLAs and reconciling pull counts against invoices.

Required profile

• 4+ years of experience as a data or analytics engineer, with ownership of a production data platform.
• Strong SQL expertise and data‑modeling skills (dimensional models, slowly changing dimensions, point‑in‑time snapshots).
• Hands‑on experience with a cloud data warehouse, preferably Snowflake.
• Experience with dbt, version control, code review and CI pipelines.
• Proficiency in Python for pipelines, tests and automation.
• Track record of building data‑quality tests and alerts (e.g., dbt tests, Great Expectations, Monte Carlo, Elementary).
• Experience with an orchestration tool such as Airflow, Dagster or Prefect.
• Ownership mindset and clear written communication.

Required skills

• SQL
• Snowflake
• dbt
• Python
• Airflow
• Dagster
• Prefect
• Great Expectations
• Monte Carlo
• Elementary
• Git (version control)
• CI/CD pipelines
• Data modeling

What we offer

• Full ownership of the Credit Risk data layer with the chance to shape its evolution.
• Impactful work on critical financial products in a remote‑first environment.
• Collaboration with Credit Risk, Data Science, Engineering and Product teams.
• Opportunity to work with AI‑driven tools and modern data stack technologies.