Key Responsibilities :

1. Enterprise Data Architecture & Design :

- Roadmap & Strategy : Define and own the enterprise data architecture roadmap. Design scalable Azure-based Lakehouse architectures (Databricks / Fabric).

- Data Modeling : Create and govern conceptual, logical, and physical data models. Establish naming conventions and architectural principles.

- System Integration : Design data pipelines and ingestion frameworks for complex industrial systems (ERP/SAP, MES, IoT Telemetry).

- Modernization : Drive the migration from legacy systems to modern cloud patterns, evaluating and onboarding new tools (Data Virtualization/Denodo, Streaming tech).

2. Data Governance & MDM Strategy :

- Framework Implementation : Define and implement the enterprise-wide data governance framework (based on DAMA-DMBOK principles).

- Policy & Standards : Establish data policies, ownership/stewardship models, and escalation workflows.

- Master Data Management (MDM) : Own the global MDM strategy, ensuring "golden record" consistency across plants and regions.

- Compliance : Ensure data security, lineage, and GDPR compliance are embedded "by design" in every architectural decision.

3. Data Quality & Reliability :

- Monitoring & Audits : Implement data quality rules (accuracy, consistency, completeness) and automated monitoring dashboards (e.g., using Great Expectations or similar tools).

- Observability : Define critical data elements (CDEs) and facilitate root-cause analysis for systemic quality issues.

4. Leadership & Enablement :

- Technical Mentorship : Guide data engineers on implementation patterns and best practices.

- Business Partnership : Act as a bridge between business stakeholders and technical teams to translate complex needs into scalable data products.

- Self-Service : Enable self-service analytics by designing governed semantic layers (Power BI) and enterprise data catalogs.

Required Qualifications & Skills :

- Education : Masters or PhD in Computer Science, Data Management, or Engineering.

Architecture Core :

1. Expert knowledge of Azure Data Platform (ADLS, Synapse, Databricks, Fabric).

2. Strong hands-on experience with ETL/ELT design, SQL, Python, and Spark.

Governance Core :

1. Deep understanding of DAMA-DMBOK or similar governance frameworks.

2. Experience with Data Cataloging, Business Glossaries, and RBAC security models.

- Domain Experience : 7+ years in data leadership, ideally within Manufacturing, Steel, or Industry 4.0 environments.

- Soft Skills : Excellent influence-without-authority skills; fluent in English (written/spoken).

Nice to Have :

- Certifications : TOGAF, Azure Solutions Architect, or DAMA Certified Data Management Professional (CDMP).

- Advanced Tech : Exposure to Data Virtualization (Denodo), Data Mesh architecture, or AI/ML feature stores.

- SAP Context : Familiarity with SAP (ECC/S4 HANA) and Supply Chain/Quality systems.

- Languages : Knowledge of French, Portuguese, or Dutch.