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# Data Architect - Cloud & Analytics H/F

- **Company:** Jobposting
- **Location:** France (Remote available)
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Microsoft Azure, Cloud Computing, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Security, Event-Driven Programming, Identity and Access Management, IT Management, Python (Programming Language), Meta-Data Management, Operational Data Store, SQL Databases, Data Streaming, Apache Spark, Data Lakes, Data Management, Physical Data Models, Data Lakehouse, Domain Driven Design, Databricks
- **Published:** October 10, 2026
- **Apply:** https://www.hellowork.com/fr-fr/emplois/84267174.html

## About the Role

English language proficiency required

 - Expertise in Azure and Databricks mandatory
 - Experience in designing Analytics and Advanced Analytics solutions (batch, event-driven, classical data architecture such as Medallion)
 - IT governance experience in a mature context, including architecture review processes

Le profil recherché, developmentStrong stakeholder management across business, product managers, engineers and architectsAble to challenge requirements and translate business needs into pragmatic architecture decisionsCollaboration and influencing skills in complex cross-functional environmentsExcellent communication, facilitation and workshop leadership capabilitiesDelivery-oriented mindset balancing governance, standardization and business valueCoaching and mentoring capabilities to drive architectural maturity and alignment across teamsEnglish language proficiency (mandatory)Expertise in Azure and DatabricksExperience in designing Analytics and Advanced Analytics solutions (batch, event driven, classic data architecture: Medalion)Experience in IT governance in a mature context: architecture review1 ou 2 jours sur site voir Full Remote, 1. Strong data architecture experience on modern cloud data platforms (Azure, Databricks, Data Lakehouse, SQL, APIs, event-driven integration)

 2. Expert in conceptual, logical and physical data modelling (enterprise and domain-driven modelling)
 3. Design of scalable data products, canonical data models, data flows, lineage and reusable integration patterns
 4. Hands-on understanding of data engineering frameworks (Python, Spark, SQL, Delta Lake, ETL/ELT)
 5. Experience designing APIs, low-latency data access patterns, analytics and operational data consumption solutions
 6. Strong knowledge of data governance, metadata management, security, access management and information ownership
 7. Experience with logistics, warehouse, inventory, transport, parts, planning or supply-chain business processes
 8. Ability to define architecture standards, target architectures and technology roadmaps
 9. Ability to work with AI tools/knowledge of AI tools and capabilities to boost overall performance/AI assisted development
 10. Strong stakeholder management across business, product managers, engineers and architects
 11. Able to challenge requirements and translate business needs into pragmatic architecture decisions
 12. Collaboration and influencing skills in complex cross-functional environments
 13. Excellent communication, facilitation and workshop leadership capabilities
 14. Delivery-oriented mindset balancing governance, standardization and business value
 15. Coaching and mentoring capabilities to drive architectural maturity and alignment across teams
 16. English language proficiency (mandatory)
 17. Expertise in Azure and Databricks
 18. Experience in designing Analytics and Advanced Analytics solutions (batch, event driven, classic data architecture: Medalion)
 19. Experience in IT governance in a mature context: architecture review
 20. 1 ou 2 jours sur site voir Full Remote

## Description

This role involves working with modern cloud data platforms and requires strong expertise in data architecture, particularly within Azure and Databricks environments. The position focuses on designing scalable data products and solutions, with an emphasis on analytics, data governance, and supply-chain related business processes., Design and implement data architecture on cloud platforms including Azure, Databricks, Data Lakehouse, SQL, APIs, and event-driven integration.

 - Develop conceptual, logical, and physical data models using enterprise and domain-driven approaches.
 - Create scalable data products, canonical data models, data flows, lineage, and reusable integration patterns.
 - Apply hands-on data engineering skills using Python, Spark, SQL, Delta Lake, ETL/ELT frameworks.
 - Design APIs and low-latency data access patterns for analytics and operational data consumption.
 - Ensure strong data governance, metadata management, security, access management, and information ownership.
 - Support logistics, warehouse, inventory, transport, parts, planning, or supply-chain business processes.
 - Define architecture standards, target architectures, and technology roadmaps.
 - Utilize AI tools and knowledge of AI capabilities to enhance overall performance and support AI-assisted development.
 - Manage stakeholders across business, product management, engineering, and architecture teams.
 - Challenge requirements and translate business needs into pragmatic architectural decisions.
 - Collaborate and influence in complex cross-functional environments.
 - Lead communication, facilitation, and workshops.
 - Maintain a delivery-oriented mindset balancing governance, standardization, and business value.
 - Coach and mentor teams to drive architectural maturity and alignment.

Tools & Environment

 - Azure cloud platform
 - Databricks
 - Data Lakehouse architecture
 - SQL and APIs
 - Python, Spark, Delta Lake
 - ETL/ELT frameworks
 - AI tools for development and performance enhancement
 - Data governance and metadata management frameworks, Profil recherchéStrong data architecture experience on modern cloud data platforms (Azure, Databricks, Data Lakehouse, SQL, APIs, event-driven integration)Expert in conceptual, logical and physical data modelling (enterprise and domain-driven modelling)Design of scalable data products, canonical data models, data flows, lineage and reusable integration patternsHands-on understanding of data engineering frameworks (Python, Spark, SQL, Delta Lake, ETL/ELT)Experience designing APIs, low-latency data access patterns, analytics and operational data consumption solutionsStrong knowledge of data governance, metadata management, security, access management and information ownershipExperience with logistics, warehouse, inventory, transport, parts, planning or supply-chain business processesAbility to define architecture standards, target architectures and technology roadmapsAbility to work with AI tools/knowledge of AI tools and capabilities to boost overall performance/AI assisted