Data Architect

This is a fully remote position, open to applicants in Belgium.

📋 Description

• Oversee the technical evaluation of corporate data, ETL/integration, and reporting/dashboard platforms in relation to business and technical requirements.

• Convert business and migration needs into technical specifications and target data architectures.

• Assess current 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 strategies, including transition scenarios, data mappings, sequencing, validation, cutover, and coexistence.

• Prepare and facilitate technical proofs of concept.

• Prepare and oversee the technical implementation of migrations alongside BI/DWH teams and service providers.

• Create data integration solutions using ETL/ELT processes and tools.

• Develop or modify jobs and pipelines to meet migration and operational requirements.

• Create, modify, and enhance conceptual, logical, and physical data models.

• Conduct hands-on database analysis, SQL, data profiling, mapping, ETL/ELT development, troubleshooting, validation, optimization, and migration.

• Monitor and enhance data systems, databases, and pipelines for performance, scalability, and reliability.

• Maintain and refine technical and business metadata, data lineage, and documentation.

• Implement data profiling, validation, and cleansing processes.

• Contribute to data governance concerning data quality, lineage, access controls, metadata, and data cataloging.

• Collaborate with business users, data engineers, BI and AI specialists, and other technical teams.

• Enhance data suitability for AI and agentic use by establishing appropriate structures, identifiers, relationships, metadata, and provenance.

• Evaluate and prototype modern data management technologies, including SQL/NoSQL databases and semantic or graph-based representations.

• Share knowledge and promote best practices, standards, and tools across BI/DWH, data, and AI teams.

• Stay updated on advancements in data platforms, integration, analytics, and AI-related data architecture.

⛳️ Requirements

• A university degree (EQF 6: Bachelor's level or equivalent).

• At least 12 years of professional IT experience.

• Minimum of 2 years’ experience in enterprise data architecture and platform assessment, covering BI, data, and integration environments.

• At least 2 years of hands-on experience with enterprise relational databases/DWH, including SQL analysis, troubleshooting, and performance optimization.

• Minimum of 2 years of hands-on experience with ETL/ELT and data integration tools, including developing, modifying, and troubleshooting pipelines.

• At least 2 years of experience applying data modeling across conceptual, logical, and physical layers, including 3NF, Data Vault, and dimensional/star-schema approaches.

• Minimum of 1 year involved in enterprise data/BI/DWH migrations.

• Proficiency in understanding, speaking, and writing in English.

• Knowledge of French would be considered an asset.

• Ability to work effectively within a team as well as independently.

• Capacity to participate in multilingual meetings.

• Excellent interpersonal and communication skills.

• Results-oriented mindset with a focus on delivering outcomes.

• Strong experience in assessing data, data integration/ETL, and reporting/BI platforms.

• Proven experience in designing, preparing, and supporting enterprise data and BI/DWH migrations.

• Significant hands-on experience with enterprise relational databases and SQL-based data warehouse environments.

• Experience with Oracle environments is particularly relevant.

• Strong knowledge and practical experience with ETL/ELT, data transformation, orchestration, and batch-processing pipelines.

• Profound knowledge of relational/3NF and dimensional/star-schema data modeling.

• Experience with enterprise BI and reporting architectures.

• Familiarity with 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, cataloging, 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.

• Familiarity with enterprise data architecture methods, standards, and documentation practices.

• Understanding of requirements for AI- and agentic-ready enterprise data.

• Knowledge of semantic modeling, knowledge graphs, and ontology-based approaches is an advantage.

• Certification in TOGAF, CDMP, DAMA-DMBoK, or ISO data governance standards, or equivalent, is mandatory.

• Ability to work effectively across business, BI/DWH, data engineering, and AI teams.

🏝️ Benefits

• Comprehensive health insurance plan from day one.

• Meal allowance provided through a ticket restaurant card.

• Opportunity to work on impactful projects at a national and European level.

• Access to in-house training sessions.

• A wide range of online learning opportunities.

• A collaborative culture that regularly celebrates achievements and milestones.