Credit Data Engineer
at Klarna
Posted a month ago
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- Compensation
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- City
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Currency: Not specified
You will own the global underwriting (UW) tables and be accountable for freshness, completeness, accuracy and data lineage. You'll design agent- and human-friendly data models and machine-readable data contracts, and build/run batch and streaming pipelines powering scoring, real-time decisioning, monitoring and underwriting optimization. The role also includes implementing observability, incident management and partnering closely with credit, policy, modeling, treasury and finance teams to deliver consumer-centric models and regulatory reporting.
What you’ll do
Own the global UW tables (canonical facts/dimensions for applications, decisions, features, repayments, delinquency) with clear SLAs for freshness, completeness, accuracy, and data lineage.
Design for AI-agents and humans: consistent IDs, canonical events, explicit metric definitions, rich metadata (schemas, data dictionaries), and machine-readable data contracts.
Build & run pipelines (batch + streaming) that feed UW scoring, real-time decisioning, monitoring, and underwriting optimization.
Instrument quality & observability (alerts, audits, reconciliation, backfills) and drive incident/root-cause reviews.
Partner closely with Credit Portfolio Management, Policy teams, Modeling teams, and treasury and finance teams to land features for RUE and consumer-centric models, plus regulatory and management reporting.
Tech stack (what we use)
Languages: SQL, PySpark, Python
Frameworks: Apache Airflow, AWS Glue, Kafka, Redshift
Cloud & DevOps: AWS (S3, Lambda, CloudWatch, SNS/SQS, Kinesis), Terraform; Git; CI/CD
What you’ll bring
Proven ownership of mission-critical data products (batch + streaming).
Data modeling, schema evolution, data contracts, and strong observability chops.
Familiarity with AI/agent patterns (agent-friendly schemas/endpoints, embeddings/vector search).
