Data Engineer / Data Platform Architect (w/m/d)

Bausparkasse Mainz • Mortgage Lending & Brokers • SQL • ETL/ELT • Data Vault • Dimensional Modeling • 30 days ago
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Salary
≈ $86k – $207k per year (Estimated)
Location
In office (Mainz)
Seniority
Staff
Employment
Full-Time

First seen by Alion on Sep 25, 2026.

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Bausparkasse Mainz

Bausparkasse Mainz is a German building society that offers home financing, building savings contracts and support with property purchases. It hires data engineers and data platform architects for its financial services IT environment. The company is headquartered in Mainz, Germany.
bkm.de • HQ: Mainz, Germany • Commercial & Retail Banks • Mortgage Lending & Brokers
  • Sie entwickeln die Zielarchitektur unserer Datenplattform – vom klassischen DWH hin zu einer integrierten Lösung für Reporting, BI und Data Science (z. B. Data Lake/Lakehouse).
  • Sie modellieren fachlich und technisch tragfähige Datenmodelle (z. B. relational, dimensional, ggf. Data Vault) und verantworten zentrale Datenmodelle für Kernprozesse.
  • Sie konzipieren und implementieren ETL-/ELT-Strecken und Data Pipelines zur Anbindung unserer Quellsysteme – abstimmbar, performant, robust und automatisiert.
  • Sie arbeiten eng mit Fachbereichen zusammen, um datengetriebene Use Cases von der Anforderung bis zur produktiven Umsetzung zu begleiten.
  • Sie stellen Datenqualität, Transparenz und Governance sicher (z. B. Metadatenmanagement, Data Lineage, Datenschutz).
  • Sie übernehmen Verantwortung für den Betrieb, das Monitoring und die kontinuierliche Verbesserung unserer Datenplattform.
  • Mehrjährige Erfahrung als Data Engineer, DWH-Entwickler:in oder Data Platform Architect in komplexen Unternehmensumgebungen, idealerweise im Finanzdienstleistungsumfeld.
  • Sehr gute Kenntnisse in SQL sowie in Datenmodellierung und Datenbankdesign (z. B. Star-/Snowflake-Schema, Normalisierung).
  • Fundierte Erfahrung mit ETL-/ELT-Prozessen und gängigen Tools/Frameworks zur Datenintegration und -orchestrierung.
  • Praxiserfahrung mit modernen Datenplattformen, z. B. Cloud-DWH (Redshift, BigQuery, Snowflake), Data-Lake-/Lakehouse-Konzepten oder vergleichbaren On-Premises-Technologien.
  • Ausgeprägte Kommunikationsfähigkeit, Freude an der Zusammenarbeit mit Fachbereichen und die Fähigkeit, komplexe Sachverhalte verständlich zu vermitteln.
  • Strukturierte, eigenverantwortliche Arbeitsweise und hohes Qualitätsbewusstsein.
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