Data Architect

Description

The company is Arηs Group, part of Accenture, and is hiring a Data Architect to support a client's data and analytics transformation within the EU institutions in Brussels.

The work is to assess and modernise the client's existing Business Intelligence (BI), Data Warehouse (DWH), data integration and reporting environments, and to draw up a roadmap toward future data platforms and AI-ready data architectures.

The setting is international and multicultural, and calls for strong technical skills, professionalism and close attention to data governance and quality.

You will evaluate current data ecosystems, define target architectures, support migrations, and improve data quality, metadata management and integration.

Responsibilities

• Lead the technical assessment of proposed corporate sovereign data, ETL/integration and reporting/dashboarding platforms against the client's business needs, data landscape, technical specifics, performance, scalability, security and integration requirements.
• Turn business and migration needs into technical specifications and target data architectures that meet both immediate operations and longer-term change.
• Analyse the existing BI/DWH architecture, including databases, data models, ETL processes, integrations, reports and dashboards, to find dependencies, gaps, migration limits and technical risks.
• Design the target architecture and migration approach, covering transition scenarios, data mappings, dependencies, sequencing, validation, cutover and, where needed, coexistence of old and new solutions.
• Prepare and support technical proofs of concept that test proposed solutions against representative client use cases and data.
• Prepare and monitor the technical execution of migrations with the BI/DWH team and corporate service providers, protecting data integrity, service continuity and a successful transition.
• Design data integration solutions using ETL/ELT processes and tools, and build or adapt the jobs and pipelines needed for migration and day-to-day operations.
• Create, adapt and optimise conceptual, logical and physical data models for current and target environments.
• Do hands-on work when needed: database analysis, SQL, data profiling and mapping, ETL/ELT development, troubleshooting, validation, optimisation and migration, plus monitoring and tuning of data systems, databases and pipelines for performance, scalability and reliability.
• Maintain and improve technical and business metadata, data lineage and documentation to support accuracy, traceability, integration and reuse.
• Put data profiling, validation and cleansing processes in place to keep data accurate, consistent and reliable.
• Help shape data governance practice, covering data quality, lineage, access controls, metadata and cataloguing, in line with client standards and services.
• Work with business users, data engineers, BI and AI specialists and other technical teams so that data architectures meet operational and emerging needs.
• Help make the client's data usable by AI and agentic systems through suitable structures, identifiers, relationships, metadata, provenance and other machine-readable representations, while staying compatible with established BI and data management needs.
• Assess and, where useful, prototype modern data management technologies and approaches, including SQL and NoSQL databases and semantic or graph-based representations, where they clearly add value for the client's use cases.
• Share expertise and promote good practices, standards and tools across the BI/DWH, data and AI teams, and contribute as a hands-on team member.
• Follow developments in data platforms, integration, analytics and AI-related data architecture, and judge how practical they are for the client.

Requirements

• University degree at EQF level 6 (Bachelor's level) or equivalent.
• At least 12 years of professional IT experience.
• Ability to tell a clear story when communicating data architecture.
• Ability to balance long-term business goals with technical feasibility, guiding project vision and validating architecture decisions.
• Ability to understand, speak and write English.
• Knowledge of French is considered an asset.
• Ability to work both in a team and independently.
• Ability to take part in multilingual meetings.
• Strong interpersonal and communication skills.
• Focus on results and delivery.
• At least 2 years in enterprise data architecture and platform assessment across BI, data and integration environments.
• At least 2 years working hands-on with enterprise relational databases or DWHs, including SQL analysis, troubleshooting and performance tuning.
• At least 2 years working hands-on with ETL/ELT and data integration tools, building, adapting and fixing pipelines.
• At least 2 years applying data modelling at conceptual, logical and physical levels, including 3NF, Data Vault and dimensional/star-schema approaches.
• At least 1 year involved in enterprise data, BI or DWH migrations.
• Strong experience assessing data, integration/ETL and reporting/BI platforms against concrete business and technical requirements, including functional fit, architecture, interoperability, performance, scalability, security, migration complexity and operational constraints.
• Proven experience designing, preparing and supporting migrations of enterprise data and BI/DWH environments: reviewing architectures, dependencies and interfaces, defining target architectures and transition scenarios, data mapping, migration sequencing, validation, cutover and coexistence strategies.
• Strong hands-on experience with enterprise relational database and DWH environments, especially SQL-based systems, covering database analysis, troubleshooting, performance optimisation and data migration. Oracle experience is particularly relevant.
• Strong knowledge and practical experience of data integration patterns and tools, including ETL/ELT, transformation, orchestration and batch pipelines. Ability to directly analyse, develop, adapt and troubleshoot ETL/ELT processes is required.
• Strong knowledge of data modelling, including relational/3NF and dimensional/star-schema, with practical experience creating and adapting conceptual, logical and physical models for operational, analytical and migration purposes.
• Experience with enterprise BI and reporting architectures, including data models, semantic or metrics layers and the interfaces behind dashboards and corporate reporting. Experience migrating between BI or reporting platforms is an advantage.
• Knowledge of modern data platform and warehouse or lakehouse architectures, and the ability to judge their fit and migration impact in an enterprise, including interoperability with existing relational databases, DWHs, ETL processes and BI solutions.
• Experience with relational data stores and knowledge of other representations and stores, including NoSQL and graph approaches, with an understanding of when they add concrete value.
• Knowledge of metadata management, data lineage, cataloguing, master/reference data and data quality practices, and how to apply them to reliable integration, migration, traceability and reuse.
• Experience with data profiling, validation, reconciliation and quality controls, especially in transformation and migration work, ensuring completeness, consistency and integrity between source and target.
• Understanding of privacy, security and compliance requirements for enterprise data platforms, including access control, encryption, data residency, backup and recovery, and business continuity.
• Knowledge of API and interoperability standards for data access and system integration, including SQL and REST interfaces.
• Experience with DataOps and software engineering practices for data platforms, including version control, automated testing, deployment and environment promotion.
• Knowledge of enterprise data architecture methods, standards and documentation practices, applied pragmatically and in proportion rather than for their own sake.
• Understanding of what is needed to make structured and unstructured enterprise data usable for AI and agentic systems, including stable identifiers, entities and relationships, metadata, provenance and machine-readable semantics.
• Knowledge of semantic modelling, knowledge graphs and ontology-based approaches is an advantage, especially where they complement relational and analytical architectures and support AI use cases.
• Ability to work across business, BI/DWH, data engineering and AI teams, translating between business needs and technical delivery while contributing directly to practical technical work.
• Mandatory: one of TOGAF, CDMP, DAMA-DMBoK or ISO data governance standards, or an equivalent certification.

Conditions

Work takes place in Brussels, within the EU institutions environment.

The posting states an international, multicultural and collaborative setting.

Equal opportunity commitment is standard for this employer.

Benefits

• Competitive and attractive salary package.
• Comprehensive health insurance from day one.
• Meal allowance provided through a ticket restaurant card.
• Work on projects with impact at national and European level.
• In-house training sessions and a wide range of online learning opportunities.
• A collaborative culture where achievements and milestones are celebrated together.