Data Architect

• Lead technical assessment of corporate data, ETL/integration and reporting/dashboarding platforms against business and technical requirements
• Translate business and migration requirements into technical specifications and target data architectures
• Analyze existing BI/DWH architectures, databases, data models, ETL processes, integrations, reports and dashboards
• Identify dependencies, gaps, migration constraints and technical risks
• Design target architectures and migration approaches, including transition scenarios, data mappings, sequencing, validation, cutover and coexistence
• Prepare and support technical proofs of concept
• Prepare and monitor technical implementation of migrations with BI/DWH teams and service providers
• Design data integration solutions using ETL/ELT processes and tools
• Develop or adapt jobs and pipelines for migration and operational needs
• Create, adapt and optimize conceptual, logical and physical data models
• Perform hands-on database analysis, SQL, data profiling and mapping, ETL/ELT development, troubleshooting, validation, optimization and migration
• Monitor and optimize data systems, databases and pipelines for performance, scalability and reliability
• Maintain and improve technical and business metadata, data lineage and documentation
• Implement data profiling, validation and cleansing processes
• Contribute to data governance covering data quality, lineage, access controls, metadata and data cataloguing
• Collaborate with business users, data engineers, BI and AI specialists and other technical teams
• Improve data suitability for AI and agentic use through appropriate structures, identifiers, relationships, metadata and provenance
• Assess and prototype modern data-management technologies, including SQL/NoSQL databases and semantic or graph-based representations
• Share expertise and promote good practices, standards and tools across BI/DWH, data and AI teams
• Stay current with developments in data platforms, integration, analytics and AI-related data architecture

• University degree (EQF 6: Bachelor's level or equivalent)
• Minimum 12 years of professional IT experience
• Minimum 2 years’ experience in enterprise data architecture and platform assessment, including BI, data and integration environments
• Minimum 2 years hands-on with enterprise relational databases/DWH, including SQL analysis, troubleshooting and performance optimization
• Minimum 2 years hands-on with ETL/ELT and data integration tools, developing, adapting and troubleshooting pipelines
• Minimum 2 years applying data modelling across conceptual, logical and physical layers, including 3NF, Data Vault, dimensional/star-schema approaches
• Minimum 1 year involved in enterprise data/BI/DWH migrations
• Ability to understand, speak and write English
• Knowledge of French would be considered an asset
• Ability to work in a team as well as autonomously
• Ability to participate in multilingual meetings
• Excellent interpersonal and communication skills
• Results-oriented mindset, focused on delivering
• Strong experience assessing data, data integration/ETL and reporting/BI platforms
• Proven experience designing, preparing and supporting enterprise data and BI/DWH migrations
• Strong hands-on experience with enterprise relational databases and SQL-based data warehouse environments
• Experience with Oracle environments particularly relevant
• Strong knowledge and practical experience with ETL/ELT, data transformation, orchestration and batch-processing pipelines
• Strong knowledge of relational/3NF and dimensional/star-schema data modelling
• Experience with enterprise BI and reporting architectures
• Knowledge of modern data platform and warehouse/lakehouse architectures
• Experience with relational data stores and knowledge of NoSQL and graph-based approaches
• Knowledge of metadata management, data lineage, cataloguing, master/reference data and data quality practices
• Experience with data profiling, validation, reconciliation and quality controls
• Understanding of privacy, security and compliance requirements for enterprise data platforms
• Knowledge of API and interoperability standards, including SQL and REST-based interfaces
• Experience with DataOps and software-engineering practices, including version control, automated testing, deployment and environment promotion
• Knowledge of enterprise data architecture methods, standards and documentation practices
• Understanding of requirements for AI- and agentic-ready enterprise data
• Knowledge of semantic modelling, knowledge graphs and ontology-based approaches is an advantage
• Mandatory: TOGAF, CDMP, DAMA-DMBoK, or ISO data governance standards certification, or equivalent
• Ability to work effectively across business, BI/DWH, data engineering and AI teams

• Comprehensive health insurance plan from day one
• Meal allowance through a ticket restaurant card
• Impactful projects at national and European level
• In-house training sessions
• Wide range of online learning opportunities
• Collaborative culture with regular celebration of achievements and milestones