Data Architect

We are looking for a Data Architect to contribute to the design, implementation, governance, industrialization, and evolution of a modern Azure-based Data Platform supporting Smart City use cases, including Digital Twins, IoT data streams, geospatial data integration, advanced analytics, and AI/ML capabilities.

The consultant will play a hands-on architecture role combining enterprise data architecture, Azure cloud engineering, CI/CD automation, data governance, security, and AI/ML platform integration.

This is a full-time assignment requiring regular on-site presence in Brussels (minimum two days per week).

Your missions:

Azure Data Platform Architecture

• Contribute to the implementation and evolution of an enterprise Azure Data Architecture.
• Design scalable, secure, and governed data platforms supporting business and operational analytics.
• Define data architecture standards and best practices across the platform lifecycle.

Digital Twin & Smart City Initiatives

• Contribute to Digital Twin projects leveraging IoT, geospatial, BIM, and contextual data.
• Design architectures enabling near real-time ingestion, processing, and exploitation of sensor data.
• Support urban analytics and predictive use cases through integrated digital twin environments.

Data Platform Industrialization

• Implement and enhance CI/CD processes for Azure Data Platform components.
• Promote Infrastructure as Code practices and platform automation.
• Ensure platform reliability, repeatability, and lifecycle management across environments.

Your activities:

Data Architecture & Modeling

• Design end-to-end data architectures from ingestion to consumption.
• Define and implement:
• Lakehouse architectures
• Medallion architecture
• Dimensional models
• Data Vault approaches where appropriate
• Design Master Data Management (MDM) and Enterprise Data Management (EDM) solutions.
• Architect service and consumption layers supporting reporting and analytics.

Azure Data Platform Design

• Architect and implement solutions using:
• Azure Data Lake
• Azure Data Factory
• Azure Synapse Analytics
• Azure Databricks
• Azure SaaS data services
• Implement incremental ingestion strategies and orchestration patterns.
• Support real-time and batch processing workloads.

IoT, Geospatial & Digital Twin Integration

• Design ingestion architectures for IoT sensor streams.
• Integrate heterogeneous data sources including:
• IoT devices
• Geospatial datasets
• BIM data
• Open data platforms
• Enterprise systems
• Define semantic standardization and urban data models.
• Manage latency, data quality, and real-time processing requirements.
• Connect real-time processing layers with historical analytical platforms.

AI/ML Platform Architecture

• Design and operate AI/ML layers within the data platform.
• Integrate:
• Model development environments
• Training pipelines
• Model registries
• Inference services
• MLOps processes
• Monitoring frameworks
• Ensure AI/ML services are aligned with platform governance and security standards.
• Implement model lifecycle management, drift detection, and retraining processes.

Data Governance

• Implement governance frameworks and metadata management.
• Work with Microsoft Purview capabilities including:
• Data cataloging
• Data lineage
• Data classification
• Data quality management
• Manage data access governance and compliance requirements.

CI/CD & Infrastructure as Code

• Design and implement CI/CD pipelines using Azure DevOps.
• Deploy and manage platform resources using Terraform or equivalent IaC solutions.
• Automate provisioning, promotion, testing, and release processes.
• Support blueprint-driven deployments and reusable infrastructure patterns.

Security & Cloud Platform Governance

• Implement cloud security best practices including:
• RBAC (Entra ID)
• Private Endpoints
• Virtual Network integration
• Key Vault
• Security policies
• Design secure network topologies and environment segregation.
• Manage secrets, execution agents, private execution pools, and deployment controls.

Platform Evolution & Migration

• Support high-risk platform transformations and migrations.
• Evolve production data models while maintaining service continuity.
• Manage migration activities involving:
• Catalog changes
• Technology stack migrations
• Data model evolution
• Governance framework transitions
• Define cutover strategies, control points, testing approaches, and rollback plans.

Architecture Leadership & Knowledge Transfer

• Define and enforce architecture standards.
• Conduct architecture reviews and technical governance activities.
• Manage technical debt and architectural roadmaps.
• Produce architecture documentation and decision records.
• Collaborate with internal teams, delivery partners, and business stakeholders.
• Support knowledge transfer and capability development within internal teams.

You have the following skills:

Azure Data Platform

• Azure Data Lake
• Azure Data Factory
• Azure Synapse Analytics
• Azure Databricks
• Azure-based data platform ecosystems

Data Architecture & Modeling

• End-to-end data architecture
• Lakehouse architecture
• Medallion architecture
• Dimensional modeling
• Data Vault
• ELT / ETL processes
• MDM / EDM architectures
• ESB / API integrations

DevOps & Automation

• Azure DevOps
• Infrastructure as Code (Terraform or equivalent)
• CI/CD platform implementation
• Environment promotion and release management

Digital Twins & Smart City

• Digital Twin architectures
• IoT data ingestion and processing
• Geospatial data integration
• BIM integration
• Smart City platforms
• Real-time sensor data management

AI/ML & MLOps

• AI/ML platform architecture
• MLOps practices
• Model deployment and monitoring
• Predictive analytics platforms
• Integration of AI/ML within enterprise data ecosystems

Data Governance

• Microsoft Purview
• Data cataloging
• Data lineage
• Data classification
• Data quality management

Reporting & Analytics

• Power BI
• Semantic models
• Security models for analytics consumption

Cloud Security

• RBAC / Entra ID
• Private Endpoints
• VNet Integration
• Azure Key Vault
• Cloud networking
• Security policies and governance

• Proven experience architecting and delivering Azure-based Lakehouse platforms in production.
• Experience implementing governance frameworks using technologies such as Unity Catalog and enterprise data catalog solutions.
• Experience deploying enterprise Data & AI platforms fully through Infrastructure as Code and Azure DevOps CI/CD pipelines.
• Experience designing real-time IoT and geospatial data architectures feeding Digital Twin or Smart City solutions.
• Experience implementing and operating production AI/ML platforms with end-to-end MLOps practices.
• Experience evolving production data models and managing high-risk migrations while ensuring business continuity.

Languages

• Native or bilingual proficiency in French or Dutch
• Professional working proficiency in English