In this role you will build and operate Klarna's analytical data processing platforms on AWS, enabling large-scale batch and analytical workloads. You will shape data pipelines, table structures, and access patterns to support analytics, model training, and downstream consumption. You'll evolve platform architecture for scale, cost efficiency, security, and reliability, while leading cross-team data initiatives and upholding high code quality and operational excellence.
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- Build and operate analytical data processing platforms on AWS to support batch and analytical workloads
- Design robust data pipelines, table structures, and access patterns for analytics, model training, and downstream consumption
- Evolve platform architecture and AWS foundations for scale, cost efficiency, security, and reliability
- Lead core data processing system design using AWS Glue, Spark, S3, Iceberg, Databricks, and Redshift

- Set high standards for code quality, maintainability, and production readiness
- Drive architectural decisions with awareness of the broader data landscape and cross-team dependencies
- Design and evolve IAM models, roles, and access patterns for secure, scalable data platform use
- Identify and resolve complex performance, scalability, cost, security, and compliance challenges
- Act as a technical leader in cross-team initiatives, delivering production-ready solutions
- Extensive experience building analytical data platforms on AWS with Spark processing and S3-backed data lakes
- Strong Python skills, distributed data processing, and infrastructure-as-code (Terraform) experience
- Experience with modern table xrdztoy formats (Iceberg) and data warehouses (Redshift)
- Experience designing and operating IAM and AWS account setups for data platforms
- Product-oriented mindset focused on durable, scalable solutio

Lead Data Engineer

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