14 set - Milano
Klarna
OverviewIn this role you own the global underwriting data fabric, ensuring canonical facts and dimensions with clear SLAs.
You design for both AI agents and human users, defining consistent IDs, events, and machine-readable data contracts.
You build and run batch and streaming pipelines that feed underwriting scoring, real-time decisioning, and monitoring, while ensuring quality and observability.
You collaborate with Credit Portfolio Management and Modeling teams to land features for RUE and consumer-centric models and regulatory reporting.
This is a scale-focused data engineering role at Klarna that shapes how data supports underwriting and risk decisions.
ResponsabilitàOwn global underwriting tables (canonical facts/dimensions) with SLAs for freshness, completeness, accuracy, and data lineage
Design data schemas and contracts for AI-agents and humans, including metadata and machine-readable contracts
Build and run batch + streaming pipelines feeding underwriting scoring, real-time decisioning, monitoring, and optimization
Instrument quality and observability (alerts, audits, reconciliation, backfills) and lead incident/root-cause reviews
Collaborate with Credit Portfolio Management, Policy, Modeling, treasury/finance to land features for risk models and reporting
Requisiti fondamentaliProven ownership of mission-critical data products (batch + streaming)
Data modeling, schema evolution, data contracts, strong observability
Familiarity with AI/agent patterns (agent-friendly schemas/endpoints, embeddings/vector search)
strong collaboration
ownership
communication
SQL
PySpark
Python
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