Data Architect

Découvrez en détail les missions, compétences requises

et opportunités d’évolution

Description de la fonction

The Data Architect defines the overall technical vision for the data ecosystem. He selects the right technologies (Cloud, SQL, NoSQL), sets modeling standards and ensures the different systems (CRM, ERP, Web Platform) can exchange data seamlessly. This role — often titled in English in ESNs, scale-ups and international groups — focuses on aligning data infrastructure with 3-to-5-year business ambitions while enforcing governance, security and compliance across the entire data landscape. Au quotidien, le Data Architect collecte, structure et analyse les données pour produire des insights actionnables à destination des équipes métier. Il contribue à la gouvernance des données et accompagne la montée en maturité data de l’organisation.

Exemples d'objectifs attendus

Architecture Design : Design the global data schema (Master Data Management) to eliminate silos across departments.
Technology Selection : Arbitrate between storage solutions (Data Lake, Data Warehouse, Lakehouse) and processing tools.
Governance & Security : Define access controls, data classification and GDPR-compliant anonymization policies.
Standardization : Establish naming conventions and semantic standards so all teams work on the same data foundation.
Cloud Migration : Lead the transition from on-premise legacy systems to modern cloud-native data platforms (Snowflake, Databricks, BigQuery).

Compétences nécessaires

Hard skills:

Data modeling (UML, Merise, Dimensional Modeling, Data Vault)
Cloud data platforms (AWS, Azure, GCP) and modern lakehouse tools (Snowflake, Databricks, dbt)
SQL/NoSQL databases, streaming architectures (Kafka, Kinesis)
Microservices and API design patterns
Data governance frameworks (DAMA, DCAM) and GDPR compliance
Maîtrise de Python et/ou SQL pour l’analyse et la modélisation
Connaissance des plateformes cloud data (AWS, GCP, Azure)
Outils de visualisation (Tableau, Power BI, Looker)

Soft skills:

Systems thinking and ability to maintain a long-term architectural vision
Stakeholder influence (CTO, CDO, DSI) to drive adoption of standards
Analytical mindset and capacity to synthesize complex technical trade-offs
Cross-functional collaboration with data engineers, software architects and business teams
Sens de l’organisation et rigueur dans la gestion des priorités
Autonomie et capacité à travailler en mode projet

Évolution professionnelle

D’où vient-on ? (Accès au poste)

Senior Data Engineer : Having acquired a transversal vision beyond pipeline execution.
Senior DBA (Database Administrator) : Expert in performance and large-scale data structuring.
Software Architect : Specializing in the data persistence and streaming layer.

Vers quoi évoluer ? (Après le poste)

Chief Data Officer (CDO) : Scaling from architecture to company-wide data strategy.
Enterprise Architect : Broader scope including IT, data and business processes.
Principal Consultant / Partner : Leading large-scale data transformation engagements.

Rémunération

City	Expérience	Salaire minimum	Salaire maximum
Hors Paris	Confirmé (2-5 ans)	58 000 €	72 000 €
Hors Paris	Senior (5-10 ans)	72 000 €	90 000 €
Hors Paris	Expert/Director (10+ ans)	90 000 €	120 000 €
Paris	Confirmé (2-5 ans)	65 000 €	80 000 €
Paris	Senior (5-10 ans)	80 000 €	100 000 €
Paris	Expert/Director (10+ ans)	100 000 €	140 000 €