A public transport organization is further developing its information provision into a cohesive, future-proof data and AI landscape. For this temporary assignment, an experienced Data & AI Architect is sought to independently guide the further development of the enterprise data architecture and the AI architecture.
The architect connects business needs, data, AI, applications, and technology, translating strategic and operational issues into concrete architectural choices, target visions, principles, standards, and roadmaps.
What you will do.
- Develop and realize the target architecture for data, including the strategic transition from a data lake to a modern data ecosystem, with a clear roadmap, architectural principles, governance, and implementation frameworks.
- Develop and secure the organization-wide AI architecture, including governance, security, compliance, and standards for safe, reliable, and future-proof AI applications.
- Translate business goals and information needs into data and AI capabilities, architectural choices, and concrete design principles.
- Design and review conceptual and logical data models and contribute to a consistent common information language.
- Define architectural principles, standards, and patterns for data storage, data integration, data exchange, analytics, BI, machine learning, and generative AI.
- Guide the setup and continuous development of data platforms and the positioning of data lake/lakehouse, data warehouse, streaming, and API-/event-driven data exchange.
- Elaborate architecture for data governance: ownership, classification, metadata, cataloging, lineage, data quality, access management, and lifecycle.
- Elaborate architectural frameworks for AI, including the use of reliable data sources, model and AI asset governance, traceability/lineage, access control, monitoring, and alignment with security, privacy, and compliance frameworks.
- Assess projects, PSAs, and solution designs for alignment with the data and AI target architecture and explicitly identify deviations, risks, and dependencies.
- Advise on rationalization, reuse, and standardization of data and analytics provisions, and prevent new data silos and unnecessary platform complexity.
- Support relevant initiatives, including BI/Power BI, data products, data exchange, and AI use cases.
- Actively transfer knowledge and working methods to internal architects, data specialists, and teams.
Profile
As a Data & AI Architect, you independently guide the further development of the enterprise data architecture and establish the AI architecture. You connect business needs, data, AI, applications, and technology, translating strategic and operational issues into concrete architectural choices, target visions, principles, standards, and roadmaps. You are skilled in clearly translating complex architectural issues to both management/board and engineers/data specialists.
You are independent, results-oriented, pragmatic, and strong in stakeholder management and knowledge transfer.
What they ask
- Minimum 5 years of relevant experience in data architecture in complex environments.
- Demonstrable experience as a Data Architect, Information Architect, or similar role.
- Demonstrable experience in drawing up target architectures, architectural principles, roadmaps, and decision-making documents.
- Strong knowledge of conceptual and logical data modeling, data integration, and data exchange.
- Experience with modern data platform architectures, data lake/lakehouse, data warehouse, analytics/BI, and cloud environments.
- Demonstrable knowledge of data governance, metadata management, data lineage, data quality, and master/reference data.
- Experience with architecture for AI/ML and preferably generative AI, including governance, lifecycle, monitoring, and the relationship between AI and reliable data.
- Experience with architectural methodologies and modeling, preferably TOGAF and ArchiMate.
- Able to clearly translate complex architectural issues to both management/board and engineers/data specialists.
Wishes.
- Experience with architecture for AI/ML and preferably generative AI, including governance, lifecycle, monitoring, and the relationship between AI and reliable data.
- Experience with architectural methodologies and modeling, preferably TOGAF and ArchiMate.
- Experience with a specific cloud ecosystem is a strong plus.
- Experience in mobility, public transport, asset-intensive organizations, or public services is a plus.
How to apply
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