Data Engineer (41740)

I am looking for an experienced Data Engineer to support methodological and structural updates within a credit risk data environment. The role focuses on updating RDS codes, enhancing QA checks, and translating SAS logic into Python/PySpark while ensuring full functional parity. You will collaborate with central and local teams, define and execute test cases, and document best practices to guarantee high data quality and compliance with new specifications.

🚀 Project
- implementation of methodological changes and structural adjustments in RPGDC and RDS landscape
- update of existing RDS codes to comply with new specifications
- modification and enhancement of data quality assurance checks to ensure high data correctness and completeness
- development activities including SAS-to-Python (PySpark) code translation, testing, and documentation
- translation of pre-RDS treatments (LGD & CCF) from SAS to Python provided by Local Entities
- definition and execution of test cases to validate functional and methodological parity
- documentation of implemented changes, testing evidence, and best practices
- close collaboration with central implementation teams and Local Entities on code ownership and validation
- support in coordinating testing activities across DM/CRANE and Local Entity teams
- ensuring alignment with updated specifications while managing dependencies and scope boundaries

🎯 Skills
- strong hands-on experience with SAS
- advanced SQL knowledge
- strong Python skills, ideally with PySpark
- experience with testing methodologies and test case definition
- experience with code migration or translation projects
- understanding of data quality assurance principles
- ability to ensure data correctness and completeness according to internal QA standards
- excellent English communication skills

💡 Nice to have
- knowledge of credit risk methodology
- German language