Data Engineer
Klarna Bank ABSammanfattning
This role involves managing global underwriting tables, ensuring data quality and observability, and building pipelines for underwriting scoring and decision-making. The position requires collaboration with various teams to implement features for consumer-centric models and reporting. Proficiency in SQL, PySpark, and Python, along with experience in cloud technologies and data modeling, is essential. The work is likely remote or hybrid, focusing on data-driven decision-making in a financial or aJobbet i korthet
Anställningstyp
tillsvidareanstallning
Arbetstid
heltid
Ansök senast: 2026-08-01
Publicerad: 2026-03-24
Beskrivning
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).
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).
Ansök till tjänsten
Data Engineer
OM FÖRETAGET
Klarna Bank AB
