Lead Data Engineer

Job Description:

What you will do
* Build and operate Klarna's analytical data processing platforms on AWS, supporting large-scale batch and analytical workloads.
* Design robust data pipelines, table structures, and access patterns enabling efficient analytics, model training, and downstream consumption.
* Continuously evolve platform architecture, infrastructure, and AWS account foundations to support long-term scale, cost efficiency, security, and reliability.
* Lead the design and implementation of core data processing systems using technologies such as AWS Glue, Spark, S3, Iceberg, Databricks, and Redshift.
* Set a high bar for code quality, maintainability, and operational excellence, acting as a role model for best practices in the domain.
* Drive architectural decisions with a holistic view of Klarna's data landscape, downstream consumers, and cross-team dependencies.
* Design and evolve IAM models, roles, and access patterns to enable secure and scalable use of data platforms across teams and accounts.
* Identify and solve complex problems related to performance, scalability, cost, security, and compliance.
* Act as a technical leader in cross-team initiatives, facilitating discussions, aligning stakeholders, and delivering production-ready solutions.
Who you are
* Strong experience building analytical data platforms on AWS, including Spark-based processing and S3-backed data lakes.
* Solid hands-on skills with Python, distributed data processing, and infrastructure-as-code (Terraform).
* Experience working with modern table formats (e.g. Iceberg) and data warehouses (e.g. Redshift).
* Experience designing and operating IAM and AWS account setups for data platforms, balancing security with developer usability.
* A product-oriented mindset, focused on building durable, scalable solutions rather than one-off pipelines.
* Experience operating systems in production and improving them through monitoring, incident learnings, and iteration.

Please include a CV in English.
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