Objectives • Conduct a full inventory of structured data flows containing personal data across internal applications and external interfaces
• Assess the most effective anonymization strategy: dataset export masking, database-level anonymization, row-based access controls, or views — based on technical and business constraints
• Propose and validate tooling (starting from scratch; Varonis may be evaluated as a candidate)
• Design and document the anonymization architecture for test/dev environments
• Ensure full compliance with GDPR requirements for data used in non-production environments
• Deliver clear implementation recommendations aligned with Sibelga's application ecosystem (internal and third-party)
Scope
Data types in scope
• Structured data only (databases, relational systems, exports)
• Personal data categories: names, EAN numbers, metering data, and similar identifiers
• Data volumes: to be assessed during the mission
Applications in scope
• Internal business applications containing personal data
• External-facing interfaces and supply chain / vendor data flows
• Test and development environments across all linked systems
Required Profile
Technical skills
• Proven experience in data anonymization, data masking, or data governance projects
• Strong knowledge of structured databases (SQL, data warehouses)
• Familiarity with anonymization/masking tools (Varonis, IBM Optim, Informatica, Delphix, or equivalent)
• Understanding of GDPR Article 25 (data protection by design and by default) and related technical requirements
• Ability to assess and compare anonymization approaches: static masking, dynamic masking, tokenization, generalization, pseudonymization