Data Architect

Nous recherchons pour l'un de nos clients un Data Architect sur Neuilly sur Seine.

Mission :

The Enterprise Data Manager leads the strategy, governance, and operations of the company’s data ecosystem—ensuring data is trusted, secure, discoverable, and used to drive measurable business outcomes. This role oversees enterprise data platforms, data governance frameworks, master data and metadata management, and the delivery of high‑quality data products to business stakeholders.

Data Strategy & Governance

• Define and maintain the enterprise data strategy aligned with business goals and regulatory requirements.
• Establish and run data governance councils, drive policies for data quality, access, retention, lineage, and ethical use.
• Own the enterprise data catalog and business glossary promote data literacy across functions.
• Implement and enforce data standards (naming, metadata, golden records, quality thresholds, SLAs).
  

Data Architecture & Platforms

• Partner with Enterprise Architecture to design target-state data architecture (lakehouse/warehouse, streaming, MDM, data mesh where applicable).
• Oversee selection and management of core platforms (e.g., cloud data lake/warehouse, ETL/ELT, data quality, catalog, lineage, MDM/MDG, analytics/BI).
• Ensure scalability, performance, cost optimization, and robust CI/CD pipelines for data workloads.
  

Data Operations & Quality

• Lead end-to-end data lifecycle management (ingestion, transformation, storage, serving, archival).
• Define and monitor data quality KPIs run issue triage, remediation, and continuous improvement programs.
• Implement metadata/lineage tracking to support auditability and impact analysis.
  

Data Products & Business Enablement

• Translate business requirements into prioritized, value-driven data products (datasets, marts, semantic models, APIs).
• Partner with Finance, Sales, Supply Chain, HR, and other domains to deliver trusted, self‑service analytics.
• Enable governed self-service (semantic layers, certified datasets, role-based access, training).

Qualifications :

• Bachelor’s in computer science, Information Systems, Data Science, Engineering, or related field. Masters preferred.
• Experience: 3-5+ years in data management/engineering/analytics with 3–5 years leading enterprise data teams.
  
• Proven experience in large‑scale IT/Enterprise transformation (iData Governance Framework & Policies, data platform build-out).
• Familiarity with EA frameworks (e.g., TOGAF/COBIT)
• At ease with « Security by Design » standards
• Familiar with regulations applicable to Information Systems (Risk & Compliance)
• Familiar with norms & standards applicable to IT environments ISO2700x, NIST, RGPD…)

Technicals skills

• Cloud data platforms (Azure Synapse/Databricks or AWS Redshift/Glue or GCP BigQuery/Dataflow).
  
• Experience with data mesh or distributed domain ownership models
• Familiarity with AI/ML enabling datasets, feature stores, and model governance
• ETL/ELT tools (Workato, Talend).
• Data governance & catalog (Purview, Collibra, Alation) and lineage.
• MDM/MDG (SAP MDG, Informatica MDM, Reltio), metadata and reference data management.
• BI/Analytics (ie : Power BI, Tableau), semantic layers, DAX/SQL.
• Data modeling (dimensional, data vault, lakehouse), APIs (REST/GraphQL), Python/SQL.
• Governance & Compliance: Demonstrated experience implementing data governance programs and
• Strategic thinking with pragmatic delivery focus
  
• Influence without authority stakeholder management
• Systems thinking and risk-awareness
• Clear communication—visuals + narratives for execs and engineers
• Decision discipline—Architecture Design Reviews, trade‑off analysis
• Continuous improvement mindset