Credit Risk Data Engineer

About the role

We are looking for a Data Engineer to own the data layer behind KiwiKiwi’s credit risk decisions. You will ensure that Credit Risk always has the right data, at the right time, in the right shape.

Key responsibilities

• Own the inventory of every credit data source (TransUnion, Clarity, Plaid, Prism, internal app data) and define data needs, grain, freshness, and landing locations.
• Write data contracts with integration engineers, store raw vendor responses, and monitor data freshness, volume, fill‑rate and schema.
• Set up alerts for feature fill‑rate drops, missing vendor fields, or volume deviations and track input drift for production models.
• Maintain the Credit Risk layer in Snowflake (raw, staging, mart, feature tables) and build pipelines for application, loan, performance, and vendor data.
• Implement automated data‑quality tests (keys, duplicates, ranges, referential integrity) 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 in data engineering or analytics engineering, with ownership of a production data platform.
• Expert SQL skills and strong data‑modeling abilities (dimensional models, slowly changing dimensions, point‑in‑time snapshots).
• Hands‑on experience with a cloud data warehouse, preferably Snowflake.
• Experience using dbt for transformations, version control, code review and CI.
• Proficiency in Python for pipelines, tests and automation.
• Track record of building data‑quality tests and alerts (e.g., Great Expectations, Monte Carlo, Elementary).
• Experience with orchestration tools such as Airflow, Dagster or Prefect.
• Ownership mindset and clear written communication.

Required skills

• SQL
• Snowflake
• dbt
• Airflow
• Python
• Great Expectations
• Monte Carlo
• Elementary
• Dagster
• Prefect

What we offer

• Full ownership of the Credit Risk data layer with the chance to shape its evolution.
• Critical impact on financial products and business growth.
• Remote work from Argentina, Colombia or the Dominican Republic.
• Collaboration with multidisciplinary teams across Credit Risk, Data Science, Engineering and Product.