Data Architect

Arηs Group, part of Accenture, is looking for a Data Architect to support the strategic transformation of a client's data and analytics landscape within the EU institutions in Brussels. The objective is to assess and modernize existing Business Intelligence (BI), Data Warehouse (DWH), data integration, and reporting environments while preparing a roadmap towards future data platforms and AI-ready data architectures. The environment is international, multicultural, and highly collaborative, requiring strong technical expertise, professionalism, and attention to data governance and quality.

Responsibilities

Leading the technical assessment of corporate sovereign data, ETL/integration and reporting/dashboarding platforms; Translating business and migration requirements into technical specifications and target data architectures; Analyzing the existing BI/DWH architecture to identify dependencies, gaps, migration constraints and technical risks; Designing the target architecture and migration approach; Preparing and supporting technical proofs of concept; Preparing and monitoring the technical implementation of migrations; Designing data integration solutions using ETL/ELT processes and tools; Creating, adapting and optimizing conceptual, logical and physical data models; Performing hands-on technical work, including SQL, data profiling and mapping, ETL/ELT development and troubleshooting; Maintaining and improving technical and business metadata, data lineage and documentation; Implementing data profiling, validation and cleansing processes; Contributing to data governance practices; Working closely with business users, data engineers, BI and AI specialists and other technical teams; Contributing to making the client's data suitable for AI and agentic use; Assessing and, where relevant, prototyping modern data-management technologies; Sharing expertise and promoting good practices, standards and tools; Staying abreast of developments in data platforms, integration, analytics and AI-related data architecture

Requirements

University degree (EQF 6: Bachelor's level or equivalent); Minimum 12 years of professional IT experience; Capacity to leverage storytelling in data architecture communications; Ability to synthesize long-term business objectives with technical feasibility to guide project vision and validate architectural decisions; 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; 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; Strong experience assessing data, data integration/ETL and reporting/BI platforms against business and technical requirements; Proven experience designing, preparing and supporting migrations of enterprise data and BI/DWH environments; Strong hands-on experience with enterprise relational database and data warehouse environments, in particular SQL-based systems; Experience with Oracle environments is particularly relevant; Strong knowledge of data integration patterns and tools, including ETL/ELT, orchestration and batch-processing pipelines; Strong knowledge of data modelling approaches, including relational/3NF and dimensional/star-schema modelling; Experience with enterprise BI and reporting architectures; Experience with migration between BI/reporting platforms is an advantage; 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 for data platforms; Knowledge of enterprise data architecture methods, standards and documentation practices; Understanding of requirements for making enterprise data suitable for AI and agentic use; Knowledge of semantic modelling, knowledge graphs and ontology-based approaches is an advantage; Ability to work across business, BI/DWH, data engineering and AI teams; Mandatory: One of the following or an equivalent certification: TOGAF, CDMP, DAMA-DMBoK, or ISO data governance standards

Nice to have

Knowledge of French; Experience with Oracle environments; Experience with migration between BI/reporting platforms; Knowledge of semantic modelling, knowledge graphs and ontology-based approaches

Benefits

Competitive and attractive salary package; 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 and online learning opportunities; Collaborative culture with regular celebrations of achievements and milestones