What you'll do
- Own and evolve the global feature engineering platform that powers Klarna's risk decisions and models
- Design and improve feature definitions with stakeholders to improve predictive power and accuracy of risk assessments
- Build and architect data pipelines to solve complex problems in ingestion, transformation, and real-time serving-and support what you build
- Instrument quality and observability: alerts, dashboards, canary releases, incident follow-up
- Design systems and solutions that integrate with Klarna's ecosystem of AI tooling
Tech stack
Languages: Python, SQL
Frameworks u0026amp; data: Spark (PySpark), Kafka, open table formats (Iceberg, Delta Lake), Redis
Cloud: AWS, DynamoDB, Databricks
DevOps: Terraform, Docker, CI/CD
Who you are
- Ownership-minded over mission-critical data pipelines and serving (batch + streaming + API); you maintain production systems while shipping new features
- Tech-stack flexible: you adapt to the problem, are comfortable across Python, Spark and Kafka, however also curious to explore modern tools and frameworks to challenge the status quo
- Strong on data modeling and understanding business requirements and data relationships-you translate use cases into robust pipelines and feature definitions
- You ship in time-boxed phases, scope pragmatically, and drive projects to delivery-including rescoping or stopping work that isn't delivering value
- You communicate clearly and collaborate well with stakeholders and peers; you unblock yourself and others when priorities shift
- High tempo and autonomous: you're passionate about owning products and solutions and engaged in leading projects
- Curious to explore AI-assisted development and tooling (e.g. LLMs, Copilot, Cursor) as part of your workflow
Please include a CV in English.
Curious to learn more about Klarna and what it's like to work here? Explore our
Job ID: 518381784
Originally Posted on: 4/23/2026