Cloud Architect

Role: AI Cloud Data Architect

Location: Paris, France - 3 days onsite

Job Type: Contract

We are looking for an experienced AI Cloud Data Architect to design, implement, and govern enterprise-scale data and AI platforms on cloud environments. The ideal candidate will have strong expertise in cloud-native data architectures, AI/ML platforms, data governance, and modern analytics ecosystems. This role will drive the design of scalable, secure, and resilient solutions that enable advanced analytics, Generative AI, and machine learning use cases.

Key Responsibilities

• Design and implement enterprise data architectures on Azure, AWS, or GCP.
• Define end-to-end data strategy, including ingestion, storage, transformation, governance, and consumption.
• Architect AI/ML and Generative AI platforms using cloud-native services.
• Design scalable data lakes, lakehouses, data warehouses, and real-time data processing solutions.
• Establish data governance, metadata management, security, privacy, and compliance frameworks.
• Collaborate with business stakeholders, data scientists, engineers, and product teams to deliver AI-driven solutions.
• Define data standards, architecture principles, and best practices.
• Evaluate and recommend emerging technologies related to AI, cloud, and analytics.
• Lead architecture reviews and ensure alignment with enterprise architecture standards.
• Support implementation of MLOps, DataOps, and AI governance frameworks.

Required Skills

• Strong experience in Cloud Architecture, Data Engineering, and AI Platforms.
• Expertise in Azure, AWS, or Google Cloud Platform .
• Experience designing modern data architectures including:
• Data Lakes
• Lakehouses
• Data Warehouses
• Streaming Architectures
• Hands-on experience with:
• Databricks
• Snowflake
• Azure Synapse
• Azure Data Factory
• AWS Glue
• BigQuery
• Strong knowledge of AI/ML ecosystems and Generative AI technologies.
• Experience with Large Language Models (LLMs), RAG architectures, Vector Databases, and AI Agents.
• Proficiency in Python, SQL, and distributed data processing frameworks.
• Knowledge of data security, governance, and regulatory compliance.
• Excellent stakeholder management and leadership skills.

Preferred Skills

• Experience implementing enterprise GenAI solutions.
• Knowledge of Azure OpenAI, Amazon Bedrock, Vertex AI, or similar services.
• Experience with Kubernetes, Docker, and microservices architecture.
• Familiarity with MLOps tools such as MLflow, Kubeflow, or Azure ML.
• Experience in Banking, Financial Services, or highly regulated industries.
• TOGAF, Azure Architect, AWS Architect, or Google Cloud certifications.