Senior Data Engineer at Douglas Service GmbH — Germany

About The Role

Robust data products are developed and operated by you on our central Snowflake Lakehouse platform using DBT
Along our layer architecture, you model data and implement technically sound models based on DataVault and Kimball principles
Ingestion connectors are built and maintained by you using Python and DLT, including their orchestration in Prefect
Across the entire data lifecycle, you ensure data quality and actively contribute to the further development of our quality standards
CI/CD and GitOps processes with Azure Pipelines are shaped by you - including automated testing and clean release processes
Security and governance requirements are implemented technically by you, for example RBAC, Dynamic Data Masking, anonymisation, and role-based access concepts in Snowflake
In close collaboration with Data Analysts, Analytics Engineers, platform teams, and business units, you actively drive technical standards forward

Solid experience in Data Engineering is part of your background, ideally within a modern cloud stack and in the context of agile data warehouse development
Strong SQL skills and hands-on experience with DBT in production environments are a defining part of your technical profile
Python skills are applied by you purposefully for data integration, automation, and orchestration
Experience with Snowflake, Prefect or comparable orchestration tools, as well as CI/CD processes, is part of your practical toolkit
Data modelling based on Kimball and DataVault is familiar territory for you - you understand the principles and can apply them in context
Version-based workflows - Git, pull requests, code reviews, and trunk-based development or comparable approaches - are a natural part of your professional day-to-day
Technical standards are something you develop collaboratively within the team, contributing in a structured and solution-oriented way
Fluent communication in both German and English - in writing and verbally - rounds off your profile