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Kiwi
Kiwi
51 – 200 Darbuotojai
H1B vizos rėmėjasDraudimasFintechKonsultavimas
„Kiwi“ yra finansinių technologijų įmonė, daugiausia dėmesio skirianti asmeniniam skolinimui ir kredito istorijos kūrimui. Jos skaitmeninė platforma leidžia klientams internetu pateikti paraišką paskolai iki 3 000 JAV dolerių, nepaveikiant kredito balo, taip pat siūlo lanksčias grąžinimo galimybes ir automatinius mokėjimus. „Kiwi“ apie reikalavimus atitinkančius mokėjimus taip pat praneša kredito biurams, padėdama klientams kurti geresnę kredito istoriją. Duomenų apsauga yra integruota į skolinimosi procesą.
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Darbai įmonėje

Credit Risk Data Engineer at Kiwi – Remote in Dominican Republic

Own Kiwi’s credit-risk data foundation for lending decisions, from Snowflake pipelines and data quality monitoring to reproducible modeling datasets. This remote role supports teams across the Dominican Republic, Argentina, and Colombia.

ARArgentinaCOKolumbijaDODominikos RespublikaNuotolinisVisas etatasVidutinis lygisVyresnysis specialistasPrivaloma Kalba: anglųDuomenų inžinierius
AirflowDebesijaPythonSQL

Aprašymas

  • Manage the complete inventory of credit data sources, including TransUnion, Clarity, Plaid, Prism, and internal application and loan-servicing systems
  • Specify the required data, grain, freshness, and destination for each source
  • Create data contracts with engineers responsible for vendor integrations
  • Verify that raw vendor responses are fully retained for model development and audit needs
  • Monitor source and model-input freshness, volume, fill rate, and schema
  • Configure alerts for declining feature fill rates, missing vendor fields, and unusual volume changes
  • Monitor production-model input drift in partnership with data scientists
  • Investigate data incidents, determine root causes, coordinate remediation, and track resolution
  • Own the Credit Risk layer of the Snowflake warehouse across raw, staging, mart, and feature tables
  • Develop and maintain pipelines and transformations for application, loan, performance, and vendor data
  • Ensure modeling datasets remain reproducible and protected from training-data leakage
  • Maintain the tables that power Credit Risk dashboards and governed metrics
  • Develop automated checks for keys, duplicates, value ranges, referential integrity, and source reconciliation
  • Keep documentation, data lineage, and ownership registries current
  • Support vendor governance by reviewing SLAs and reconciling pull volumes with vendor invoices

Reikalavimai

  • At least four years of data engineering or analytics engineering experience, including primary ownership of a production data platform
  • Expert-level SQL and strong data modeling capabilities, including dimensional models, slowly changing data, and point-in-time snapshots
  • Practical experience with a cloud data warehouse, preferably Snowflake
  • Experience with a transformation framework such as dbt, along with version control, code review, and CI practices
  • Python experience for building pipelines, tests, and automation
  • Demonstrated success implementing data-quality tests and alerting with dbt tests, Great Expectations, Monte Carlo, Elementary, or custom checks
  • Experience using an orchestration platform such as Airflow, Dagster, or Prefect
  • A strong ownership approach, including proactively detecting issues, tracing root causes, and driving them to resolution
  • Clear written communication skills for producing dependable data contracts, incident notes, and table documentation
  • Spanish and English fluency is helpful but not required
  • Experience with fintech or lending, credit bureau and bank data, feature tables, training datasets, model monitoring, lending compliance, BI tools, or Metabase is helpful but not required

Privalumai

  • Work on important financial products with a direct effect on customers and business growth
  • Take full ownership of Kiwi’s Credit Risk data layer and influence its development
  • Tackle substantive problems across pipelines, data quality, monitoring, and modeling datasets
  • Join a workplace where AI is becoming central to how the team works and builds
  • Collaborate with colleagues across Credit Risk, Data Science, Engineering, and Product
  • Work fully remotely

Susiję darbai

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