Credit Data Engineer

Klarna; Turbigo; In loco; EUR 60.000 - 80.000; Tempo pieno

Descrizione del lavoro

Klarna is seeking a Data Product Owner in Turbigo, Italy, responsible for managing global underwriting data tables and optimizing data pipelines. The role requires a deep understanding of data modeling, observability, and familiarity with AI patterns.

Ideal candidates will have strong expertise in SQL, PySpark, Python, and experience with cloud technologies including AWS, Terraform, and Kafka. Collaboration with diverse teams will be essential for regulatory and management reporting.

Competenze

• Proven ownership of mission-critical data products (batch + streaming).
• Data modeling, schema evolution, data contracts, and strong observability chops.
• Familiarity with AI/agent patterns.

Mansioni

• Own the global UW tables ensuring data freshness and accuracy.
• Build and run pipelines for underwriting scoring and decision-making.
• Partner with various teams to implement features and reporting.

Conoscenze

SQL

PySpark

Python

Data modeling

Observability

Strumenti

Apache Airflow

AWS Glue

Kafka

Redshift

Terraform

Git

Descrizione del lavoro

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).