Lead Credit Risk Data Platform Engineer (Remote)

kiwi; Santo Domingo; Remote; COP 291,281,000 - 420,739,000; Full time

Benefits offered by this job

Remote work

Job summary

Kiwi is seeking a Data Engineer to own the data layer behind our credit risk decisions and ensure data is available, clean, and timely for underwriting and renewal modeling. You will define data contracts, monitor data quality, and maintain end-to-end pipelines in Snowflake.

You will work with the data science and engineering teams in a fully remote setting across Argentina, Colombia, and the Dominican Republic, shaping the data architecture and governance for risk analytics.

Qualifications

• 4+ years of data engineering or analytics engineering with ownership of a production data platform.
• Expert SQL and strong data modeling skills, including dimensional models and point-in-time snapshots.
• Hands-on experience with a cloud data warehouse, ideally Snowflake.
• Experience with a transformation framework such as dbt, using version control, code review, and CI.

Responsibilities

• Own the inventory of every credit data source and define data requirements, grain, freshness, and landing location.
• Write data contracts with vendor integrations covering fields, types, null rules, and volumes.
• Monitor freshness, volume, fill rate, and schema for every source and model input, and set up alerts.
• Triage data incidents, identify root causes, and drive fixes to closure.
• Own the Credit Risk layer of Snowflake: raw, staging, mart, and feature tables; maintain data pipelines and transformations.

Skills

SQL

Data modeling

Python

Tools

Snowflake

dbt

Airflow

Python

Metabase

Job description

Kiwi is seeking a Data Engineer to own the data layer behind our credit risk decisions and ensure data is available, clean, and timely for underwriting and renewal modeling. You will define data contracts, monitor data quality, and maintain end-to-end pipelines in Snowflake.

You will work with the data science and engineering teams in a fully remote setting across Argentina, Colombia, and the Dominican Republic, shaping the data architecture and governance for risk analytics.