Senior Full-Stack Engineer - Partner Reporting / Merchant Analytics

What You Will Do

• Own and evolve data pipelines that power Klarna’s externally-facing dashboards used by hundreds of thousands of merchants worldwide.
• Participate in all Partner Reporting initiatives, optimizing data flows to improve scalability, reliability, and standardization across markets and merchant segments.
• Build and maintain ETL / ELT pipelines that transform raw Klarna event and transaction data into merchant-ready KPIs such as funnel metrics, and customer insights.
• Automate and simplify complex reporting, replacing manual or semi-automated workflows with robust, production-grade data products.
• Collaborate closely with Data Modeling, Product Analytics, and Product Engineering teams to streamline pipelines, remove unnecessary transformation layers, and improve end-to-end data efficiency.
• Apply strong SQL-based analysis and feature engineering to ensure metrics are correct, explainable, and trusted — internally and externally.
• Help shape the foundation of a merchant analytics platform that goes beyond reporting: uncovering consumer trends, identifying high-intent shoppers, measuring campaign effectiveness, and enabling data-driven recommendations for partners.
  

Tech Stack

• Python (must-have)
• SQL (must-have; complex analytical queries at scale)
• REACT (nice-to-have; basic front-end development
• Airflow (or equivalent orchestration tools)
• Batch and ELT-style pipeline patterns
• Experience with workflow schedulers, jobs, and dependency management
• AWS (S3, Redshift, IAM, etc.)
• Redshift (or similar analytical data warehouses)
• Jenkins for CI/CD and pipeline automation
• Git-based workflows and production deployment best practices
  

Who You Are

• Proven experience as a Data Engineer building and operating production-grade data pipelines.
• Strong ownership mindset over mission-critical data products, primarily batch-based, with an appreciation for scalability and reliability.
• Deep comfort with data modeling, schema evolution, metric definitions, and data quality in analytical environments.
• Hands-on experience optimizing SQL-heavy pipelines and reducing unnecessary transformation layers.
• Ability to collaborate effectively with analytics, product, and engineering stakeholders — translating business needs into durable technical solutions.
• Prior experience in fintech, payments, or regulated environments is a strong plus, but not required.
• Excellent analytical thinking, problem-solving skills, and the ability to communicate complex data concepts clearly.
  

Please include a CV in English.
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