Data Architect

HumanInTech; Brussel Hoofdstad; Hybride; EUR 90 000 - 120 000; Plein temps

Résumé du poste

HumanInTech is seeking a senior Data Architect to analyse an education organisation's data landscape, model core domains, and co-design a target architecture and implementation roadmap. The role requires collaboration with business analysts, enterprise and solution architects, solution teams and a data competence centre.

Location is Brussels with hybrid work, and the contract can be freelance or employee. The assignment runs through 2027 with a focus on establishing a robust data architecture,

Qualifications

• Expert-level conceptual and logical data modelling (ERM, UML, ArchiMate)
• Expert-level mapping of data landscapes (sources, flows, apps, reference data)
• Expert-level knowledge of data architecture paradigms (hub, lakehouse, data mesh)
• MDM, master data, data dictionary, metadata catalogue knowledge
• Experience with exchange patterns: API, event-driven, replication, analytics feeds
• Workshop facilitation and architecture decision support experience
• Knowledge of governance: roles, processes, GDPR, 'only once' principle
• Familiarity with TOGAF, ArchiMate, DAMA-DMBOK or equivalent
• Experience with data modelling/tools and data cataloguing tools
• Understanding of security and data sovereignty constraints in architecture
• Fluent French; passive English knowledge

Responsabilités

• Framing and alignment with business analysts and programme team
• AS-IS analysis of data landscape and data flows
• Domain modelling of core business objects (pupils, staff, establishments)
• Develop conceptual and logical models and data dictionaries
• Define target architecture options (hub, lakehouse, data mesh, virtualisation)
• Establish governance foundations and metadata catalogue concepts
• Break down target into work packages and define a prioritised roadmap
• Ensure knowledge transfer and handover to internal teams

Connaissances

Data modelling

Data landscape mapping

Data architecture paradigms

Data governance concepts

Workshop facilitation

Architecture decision making

TOGAF/ArchiMate knowledge

Security and sovereignty rules

Formation

Bachelor's degree or higher

Outils

Sparx Enterprise Architect

Data catalogue tools

Description du poste

What you will do

You will provide dedicated data architecture expertise to analyse the data landscape of an education organisation, produce its cartography and conceptual and logical modelling, and co-design a target data architecture and implementation roadmap with internal teams.

This is an architecture and framing assignment. You will produce models, argued options, documented decisions and an actionable roadmap. You will analyse the existing landscape, model the domain, instruct and argue data architecture options, and derive a prioritised trajectory. You will work in support of business analysts and enterprise architects, translating their business framing into data requirements and models, and in permanent coordination with solution architects who handle the application layer.

Your activities will include:

Framing and alignment

• Facilitate workshops with business analysts and the programme team
• Derive data objects from business capabilities and processes identified by business analysts and enterprise architects
• Formulate data architecture principles applicable to the programme and align them with enterprise principles

AS-IS analysis

• Inventory data sources: applications, reference data, databases, files, exchanges with administrations and establishments
• Map current flows: producers, consumers, frequencies, exchange mechanisms, dependencies
• Identify pain points: silos, redundancies, re-entry, latency, quality defects, areas without ownership

Domain modelling

• Establish conceptual and then logical models of core business objects (pupils, staff, establishments, teaching structures, etc.)
• Identify reference data, designate master systems and clarify data ownership rules
• Produce a data dictionary and associated quality rules

Target architecture

• Instruct feasible paradigms (data hub, lakehouse, federated mesh approach, virtualisation) and compare them in the context of constraints and resources
• Confront these options with enterprise architects, solution architects and the data competence centre: the target is not predetermined and must result from this collective work
• Establish usage rules for exchange and exposure patterns (API, event-driven, replication, virtualisation, analytical feeds): which pattern for which class of need and under what conditions
• Position the target architecture in relation to shared platforms and services and the organisation's data strategy
• Translate security, personal data protection, sovereignty and digital sobriety constraints into enforceable architecture rules
• Ensure the chosen architecture does not close off analytical and AI use cases (quality, traceability, data accessibility), without pre-empting specific use cases

Data governance prerequisites

• Define the minimum governance foundations needed to adopt the architecture: roles (data owner, data steward), bodies, decision processes
• Specify the expected metadata repository and documented catalogue, and access rights management
• Describe the concrete implementation of the "only once" principle for the scope

Trajectory and transfer

• Break down the target into coherent work packages and define intermediate transition data architectures
• Prioritise the roadmap according to business value and risk, in line with the programme calendar
• Ensure knowledge transfer to internal teams so that deliverables remain usable after the assignment ends

What we are looking for

Essential skills and experience

• Expert-level conceptual and logical data modelling: entity-relationship / Merise, UML, ArchiMate; dimensional modelling
• Expert-level mapping of data landscapes: sources, flows, applications, reference data; gap analysis
• Expert-level understanding of data architecture paradigms: hub, lakehouse, data mesh, data fabric, virtualisation; ability to compare them and arbitrate in a constrained context
• Expert-level knowledge of reference data and quality: MDM, master systems (SoR), data dictionary, metadata catalogue
• Confirmed experience with exchange and exposure patterns: API, event-driven, replication, virtualisation, analytical feeds; knowledge of patterns and their implications, ability to set usage rules
• Confirmed experience facilitating workshops and instructing architecture decisions
• Confirmed knowledge of data governance: roles, lifecycle, access rights, GDPR, "only once" principle
• Confirmed knowledge of architecture frameworks and canvases: TOGAF, ArchiMate, DAMA-DMBOK or equivalent
• Confirmed experience with modelling and mapping tools (such as Sparx Enterprise Architect) and data cataloguing tools
• Confirmed understanding of security and data sovereignty: translating constraints into architecture rules
• Native or fluent French; passive knowledge of English

Personal qualities

• Ability to work in a team with business analysts, enterprise architects and solution architects, and to transform their framing into exploitable data material
• Ability to propose an argued position rather than a catalogue of options, and to defend it before a decision-making body
• Ability, conversely, to be challenged: to evolve a recommendation in light of real constraints without emptying it of substance
• Aptitude to explain architecture choices to business and management stakeholders
• Strong writing skills: deliverables must be readable, structured and directly reusable after the assignment ends
• Posture as a pivot between business, technology and governance

Questions you will be asked

• Do you hold a TOGAF certification?
• Do you have knowledge of the public sector and, ideally, the education domain?
• Do you have experience mapping and modelling a data domain in a comparable public-sector organisation? If so, in what context?
• Do you have experience with canvases or frameworks to standardise this type of approach (TOGAF, ArchiMate, DAMA-DMBOK, Data Roadmap, etc.)? If so, which ones?
• Which modelling, mapping and data cataloguing tools do you master?
• Describe in a few lines your approach to moving from an AS-IS map to a prioritised, actionable target architecture.
• The programme target is not yet fixed. How do you build a target data architecture in this context, working with internal architects, and how do you instruct the decision?
• How do you position the boundary between your work as a data architect and the work of solution architects on one hand, and data engineers on the other? Illustrate with a recent assignment.

The setting

This assignment runs until the end of April 2027, starting immediately. You will work hybrid from Brussels. The working language is French; passive knowledge of English is needed.

You will collaborate with solution architects, data engineers, database administrators, platform teams, the data office, business analysts, enterprise architects and the programme management office.

You can join us for this assignment as a freelancer or as an employee of HumanInTech. Same role, same team. If you join as an employee, your employment continues beyond this assignment. When it ends, we’ll work together to find your next assignment.

Location: Brussels, hybrid

Employer / contracting party: HumanInTech

Applications close (Brussels time): September 28, 2026 at 2:00 AM

Engagement: Freelance or employed by HumanInTech

Working hours: Full-time

Experience: 6–10 years or more

Education: Bachelor's or more

Published: September 2026