Lead Data Engineer
2 giorni fa
bardi, emilia romagna, Italia
Klarna
Tempo pieno
Gratuito con email o Google
Salva questo lavoro e mantieni la tua ricerca organizzata
Crea un account gratuito per salvare lavori, creare avvisi e tornare a questa inserzione dalla tua dashboard.
Gratuito con email o Google
Continuando accetti i nostri Termini & Informativa sulla privacy.
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.
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 formats (Iceberg) and data warehouses (Redshift)
Experience designing and operating IAM and AWS
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 formats (Iceberg) and data warehouses (Redshift)
Experience designing and operating IAM and AWS