Global AI, Data & Digitalization Architect (m/f/x)

Overview

As Global AI, Data & Digitalization Architect, you shape the digital landscape across regions, translating business challenges into scalable data and AI-enabled architectures. You will partner with global and regional stakeholders to define requirements, design end-to-end solutions, and guide teams from concept to production. Your work focuses on scalable data models, governance, and responsible AI usage to deliver tangible value. This role offers global impact, strong cross-functional collaboration, and the chance to drive standardized data practices at scale.

Pay / Benefits

• unmatched opportunities for personal and professional development
• global applicability and cross-regional exposure
• diverse and inclusive culture
• Best Place to Work culture mentioned
• focus on talent attraction and development

Responsibilities

• Partner with global and regional stakeholders to translate business needs into technology requirements
• Shape scalable data and digital solutions connecting processes, data and tech
• Design robust data models with consistent standards across systems
• Define end-to-end architectures balancing scalability, security, privacy, reliability and cost
• Transform concepts into implementation-ready designs for product and platform teams
• Explore and validate ideas via proofs of concept assessing feasibility and value
• Drive global standardization with reusable data definitions and interfaces
• Assess AI and digital platforms/ vendors to choose high-value solutions

Key requirements

• 5+ years in data, analytics, architecture, digital products or enterprise tech with cross-functional scope
• Hands-on experience in modern data ecosystems; Snowflake, Databricks, Azure data services, Power BI/Tableau, Python, SQL (or equivalent)
• Strong business acumen to structure ambiguous problems across process, data and technology
• Deep data modelling, data contracts, semantic layers, metadata, MDM, data-product principles
• Enterprise and solution architecture across data, analytics, digital products and AI/GenAI, including governance, security, privacy, reliability and cost
• Product-focused with rapid prototyping and ability to produce implementable architecture specifications
• Ability to influence senior stakeholders across functions and regions
• Experience translating challenges into global data models and solutions with stakeholder buy-in

• stakeholder influencing
• clear communication
• ambiguous-problem solving
• Data modelling
• Data governance
• MDM

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