Job
- Level
- Senior
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Dusseldorf
- Working Model
- Onsite
Job Summary
In this role, you will develop robust data products on the Snowflake Lakehouse platform, model data using Data Vault and Kimball, and maintain API connectors with Python and DLT to ensure consistent data quality standards.
Job Technologies
Your role in the team
- Robust data products are developed and operated by you on our central Snowflake Lakehouse platform using DBT.
- Entlang unserer Layer-Architektur modellierst du Daten und implementierst technisch fundierte Modelle basierend auf DataVault- und Kimball-Prinzipien.
- 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.
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Our expectations of you
Qualifications
- Python skills are applied by you purposefully for data integration, automation, and orchestration.
- 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.
Experience
- 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.
- Experience with Snowflake, Prefect or comparable orchestration tools, as well as CI/CD processes, is part of your practical toolkit.
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Benefits
Health, Fitness & Fun
Food & Drink
Work-Life-Integration
Topics You Will Work On
Job Locations
About Your Employer
Douglas
Douglas ist ein führender Einzelhändler in der europäischen Beauty-Branche. Mit mehr als 2.400 Parfümerien an erstklassigen Standorten in insgesamt 26 Ländern Europas verfügt Douglas über eine starke Marktposition.
Description
- Company Size
- 250+ Employees
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Trade
Employer reviews
by devworkplaces.com
Total
(1 Review)1.8
Culture
2.0Engineering
2.0Workingconditions
2.3Career Growth
1.2
Senior Data Engineer
- Location
- Dusseldorf
- Working Model
- Onsite
- Diversity
- Open for all genders
