Senior Data Architect — Enterprise Data & Governance (Hybrid)

Philip Morris International; Albarraque; Hybride; EUR 78 000 - 123 000; Plein temps

Résumé du poste

Philip Morris International is seeking a data architect to design, develop, and govern enterprise data architectures across the organization. The role involves partnering with business and technology stakeholders to translate requirements into scalable, secure data solutions and to maintain conceptual and logical data models.

You will define best practices for data modeling, integration, metadata management, data quality, and master data management, while optimizing data flows for accessibility

Qualifications

• Advanced knowledge of enterprise data architecture, including data modeling, integration, warehousing, data lakes, and cloud data platforms.
• Experience defining enterprise data standards, governance frameworks, and architecture principles.
• Proven ability to design scalable, secure, high-performing data solutions.
• Experience creating conceptual and logical data models and aligning multiple stakeholders.

Responsabilités

• Design, develop, and maintain enterprise data architecture standards, frameworks, and governance practices.
• Partner with business and tech stakeholders to translate requirements into scalable data solutions.
• Develop and maintain conceptual and logical enterprise data models across domains and applications.

Connaissances

Data architecture

Data modeling

Data governance

Cloud data platforms

Stakeholder management

Formation

University degree in CS/IS/Engineering

Description du poste

Philip Morris International is seeking a data architect to design, develop, and govern enterprise data architectures across the organization. The role involves partnering with business and technology stakeholders to translate requirements into scalable, secure data solutions and to maintain conceptual and logical data models.

You will define best practices for data modeling, integration, metadata management, data quality, and master data management, while optimizing data flows for accessibility