IT Architect Data Architecture (Senior)

Rhox; Schaarbeek; Sur place; EUR 70 000 - 100 000; Plein temps

Résumé du poste

Rhox is seeking an experienced data architecture consultant to map the AS-IS data landscape for an education administration project in Belgium. You will analyse applications, databases and exchanges, produce an AS-IS map of sources, flows, and ownership, and model the main business objects with a data dictionary and quality rules.

You will compare target options (data hub, lakehouse, federated data mesh, virtualisation) and support a collective decision, while ensuring governance prerequisites,

Qualifications

• Senior experience in data architecture, landscape analysis and roadmaps.
• Workshop facilitation and documentation of architecture decisions.
• Map data sources, flows, applications, repositories and gaps.
• Knowledge of MDM, data dictionaries and metadata catalogs.
• Conceptual and logical data modelling (ER, Merise, UML, ArchiMate).
• Familiarity with TOGAF, ArchiMate and DAMA-DMBOK or equivalents.
• Data governance including GDPR, roles, and access rights.

Responsabilités

• Facilitate workshops and document decisions, actions and recommendations.
• Map current sources, flows, applications, repositories and ownership gaps.
• Model domain concepts and relationships; define reference data and ownership rules.
• Define data dictionary and quality rules; identify systems of record.
• Compare target architectures and present a recommended option.
• Define rules for exchange, exposure, security and privacy.
• Prioritise governance prerequisites, roadmaps and knowledge transfer.

Connaissances

Senior data architecture

Workshop facilitation

Data landscape mapping

MDM and data governance

Conceptual/logical data modelling

TOGAF/ArchiMate/DAMA-DMBOK

Data governance and GDPR

Data cataloguing tools

Outils

Sparx Enterprise Architect

Data cataloguing tools

Description du poste

The mission

This is a data architecture and framing assignment for an education administration. You will analyse applications, databases, files, repositories and exchanges, then produce an AS-IS map of sources, flows, applications, reference data and pain points. You will model the main business objects, establish a data dictionary, define quality rules, identify systems of record and clarify data ownership.

Working from business capabilities and processes identified by business analysts and enterprise architects, you translate business framing into data requirements and models. You compare target options such as a data hub, lakehouse, federated data mesh and virtualisation, then support a collective decision. The work also covers governance prerequisites, rules for exchange and exposure patterns, transition architectures and a prioritised roadmap.

Your outputs include an AS-IS data landscape map, domain model, target architecture options note, target data architecture dossier, governance prerequisites, roadmap and workshop documentation. These deliverables must support later application-level decisions by solution architects and remain usable by the participating public-sector teams. The architecture must also preserve future analytical and AI uses through data quality, traceability and accessibility, without pre-empting specific use cases.

Your responsibilities

• Facilitate workshops and document decisions, open points and recommendations.
• Map current sources, flows, applications, repositories, dependencies, ownership gaps and pain points.
• Model the domain conceptually and logically, including key business objects and relationships.
• Define reference data, systems of record, ownership rules, data dictionary and quality rules.
• Compare target architecture paradigms and present a reasoned recommendation for collective decision.
• Define architecture rules for exchange, exposure, security, privacy and data sovereignty.
• Prioritise governance prerequisites, transition architectures, work packages, roadmap and knowledge transfer.

Your profile

Essential skills

• Senior experience in data architecture, covering landscape analysis, domain modelling, target design and implementation roadmaps.
• Workshop facilitation and the preparation, explanation and documentation of architecture decisions.
• Data landscape mapping across sources, flows, applications, repositories, dependencies and gaps.
• Reference data and data quality practices, including MDM, systems of record, data dictionaries and metadata catalogues.
• Conceptual and logical data modelling using entity-relationship or Merise, UML and ArchiMate, plus dimensional modelling.
• Architecture frameworks and canvases, including TOGAF, ArchiMate and DAMA-DMBOK or equivalents.
• Data governance covering roles, lifecycle, access rights, GDPR and the only once principle.
• Modelling and mapping tools such as Sparx Enterprise Architect, plus data cataloguing tools.
• Ability to compare data hubs, lakehouses, data mesh, data fabric and virtualisation against constraints and available means.
• Knowledge of API, event-driven, replication, virtualisation and analytical ingestion patterns, including their implications and usage rules.
• Ability to translate security, personal data protection, data sovereignty and digital sobriety constraints into enforceable architecture rules.
• Ability to work with business analysts, enterprise architects, solution architects, data engineers and platform teams.
• Clear technical writing and the ability to explain and defend recommendations with business and leadership stakeholders.
• Ability to revise recommendations when challenged by actual constraints without losing their substance.

Languages

• French, native.
• English, B1.

Working context

• You work from business capabilities and processes provided by business analysts and enterprise architects, translating them into data models and requirements.
• You coordinate with solution architects on application design, and with data engineering, database and platform teams on implementation and operations.
• The target architecture is assessed collectively. You present options and a motivated recommendation rather than imposing a design.
• The assignment defines governance prerequisites without replacing the existing data governance operating model, and includes knowledge transfer to public-sector and education teams.