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# Senior-Data-Engineer-m-w-d

- **Company:** CHG-MERIDIAN
- **Location:** Weingarten, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Vault Modeling, DevOps, Disaster Recovery, Python (Programming Language), Scrum Methodology, SAP (Applications), SQL Databases, Transact-SQL, Azure Data Factory, Git, Microsoft Fabric, Pyspark, Information Technology, Servicenow
- **Published:** September 18, 2026
- **Apply:** https://www.stepstone.de/stellenangebote--Senior-Data-Engineer-m-w-d-Weingarten-CHG-MERIDIAN--14519969-inline.html

## About the Role

* Erfahrung: 5+ Jahre in Data Engineering oder Data Platform Rollen; abgeschlossenes Studium in Informatik, Wirtschaftsinformatik oder vergleichbar
 * Core Platform & Programmierung: Microsoft Fabric (erforderlich), Azure Data Factory, MS Purview (Grundkenntnisse); SQL, Python/PySpark, T-SQL
 * Datenmodellierung & DevOps: Data Vault, Dimensional Modeling, Medallion Architecture; CI/CD, Git, Azure DevOps, ServiceNow
 * Methoden & Domänenwissen: Agile/Scrum, ETL-Prozesse, Data Mesh-Prinzipien, Data Product Design
 * Soft Skills: Coaching-Kompetenz, Team-Enablement, ausgeprägte Kommunikationsstärke
 * Sprachkenntnisse: sehr gute Englisch- und Deutschkenntnisse in Wort und Schrift

## Description

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 * Microsoft Fabric Transformation & Architektur: Mitgestaltung der Modernisierung unserer Datenarchitektur; Definition von Standards und Best Practices; hands-on Entwicklung von Referenzimplementierungen; Design und Implementierung der Medallion Architecture (Bronze, Silver, Gold)
 * Data Engineering & Pipeline-Entwicklung: Entwicklung und Wartung von Datenpipelines für Ingestion und Transformation; Anbindung interner und externer Datenquellen inkl. SAP-Integration und On-Premises-Systemen; Performance-Optimierung für Storage und Query Execution
 * DevOps, CI/CD & Plattformqualität: Implementierung automatisierter Deployment-Pipelines; Aufbau von Git-Repositories; Etablierung von Data Product Thinking (Data Mesh); Einhaltung von Namenskonventionen für alle Fabric Assets; Business Continuity Planning & Disaster Recovery
 * Teamentwicklung & Zusammenarbeit: Coaching und Upskilling von 3 bestehenden BI-Entwicklern; Wissenstransfer zu KI- und Automatisierungsfähigkeiten von Microsoft Fabric; enge Zusammenarbeit mit Data Analysts, Data Scientists und BTS Operations/MS Fabric Admin

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