Data & IA engineer (F/M)
Role details
Job location
Tech stack
Job description
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Designing and deploying efficient, secure, and high-performing data pipelines within Microsoft Fabric that seamlessly integrate data from multiple enterprise sources.
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Delivering production-grade, well-structured lakehouses or warehouses optimized for analytics, machine learning, and real-time AI workloads.
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Automating ingestion, transformation, and orchestration processes using Fabric Data Pipelines, Dataflows Gen2, and supporting Azure services, ensuring low latency and high reliability.
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Implementing monitoring, testing, and CI/CD practices for data assets and AI models to ensure consistency, scalability, and compliance with data governance frameworks.
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Proactively improving performance, reliability, and cost efficiency across Fabric workloads., Data Engineering (Fabric Core)
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Implement data ingestion using Fabric Data Pipelines, Dataflows Gen2, and event-driven sources.
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Develop scalable transformations using Spark (Fabric notebooks) and SQL (Warehouse / Lakehouse).
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Model data for analytics and AI using medallion architecture (Bronze / Silver / Gold).
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Ensure data quality, lineage, and observability using Fabric monitoring and Purview integration.
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Document data pipelines, schemas, and reusable pattern.
Real-Time & Streaming
- Build real-time data pipelines using Fabric Real-Time Intelligence and other Integration technologies.
- Integrate event sources.
- Operate and maintain streaming architectures with failure handling.
AI Engineering
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Design and deploy RAG (Retrieval-Augmented Generation) architectures and agentic workflows using Fabric data and AI Foundry.
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Build and operate automated inference pipelines (batch and real-time) integrated directly with the Fabric Lakehouse.
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Transform AI prototypes into enterprise-grade APIs and services, ensuring scalability and low-latency performance.
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Set up tracking for model performance, token usage, and AI safety (guardrails, drift, and output quality).
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Support data scientists by operationalizing notebooks, feature engineering pipelines, and ML models within Fabric.
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Ensure compliance with responsible AI standards and auditing requirements.
Analytics & Consumption
- Enable semantic models and datasets for Power BI.
- Optimize models for performance, refresh reliability, and cost.
- Support self-service analytics while enforcing governance standards.
Platform, Governance & Operations
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Implement CI/CD for Fabric (GitHub integration, deployment pipelines).
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Apply data governance and security (Purview, RBAC, sensitivity labels).
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Optimize capacity usage and cost (Fabric capacity management).
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Ensure compliance with enterprise data and AI standards.
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Monitor pipeline health, data freshness, and usage metrics through Fabric and Azure monitoring tools.
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Participate in incident response and platform optimization initiatives.
Collaboration
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Work closely with data scientists, BI developers, architects, and product teams.
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Translate business requirements into scalable Fabric solutions.
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Contribute to platform standards, reusable assets, and documentation.
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Provide technical guidance to less experienced engineers and promote best practices.
Requirements
- Strong Python and SQL.
- Hands-on experience with Microsoft Fabric:
- Lakehouse
- Data Pipelines / Dataflows Gen2
- Fabric Spark
- Fabric Warehouse
- Solid understanding of data modeling and analytical design patterns.
- Experience with medallion architecture and performance-optimized transformations.
- Microsoft Ecosystem
- Azure services: Azure Data Factory, Event Hubs, Azure ML, Azure OpenAI.
- Power BI semantic modeling (Direct Lake, import, incremental refresh).
- Identity and security using Azure Entra ID.
- Familiarity with Purview lineage, classifications, and access governance.
- Software Engineering Mindset
- GitHub-based development and CI/CD.
- Monitoring, logging, and operational support.
- Cost-aware design (capacity sizing, workload isolation).
- Experience with unit testing for data transformations, validation frameworks, and deployment automation.
- Preferred Qualifications
- Experience with Fabric Real-Time Intelligence (KQL).
- Experience with LLM-based architectures (RAG, vector search, copilots).
- Familiarity with Microsoft Purview and enterprise data governance.
- Experience operating large-scale Fabric capacities across domains.
- Fluency in English is required; proficiency in other languages spoken in the EMEA region is a plus.
Benefits & conditions
- HR Interview
- Referral calls
- Interview with SVP Data, AI and Analytics
Work Mode & Location
- Hybrid: 3 days in Paris (8ème) after the trial period
Benefits that await you: The role - Your daily activities will be interesting, stimulating and varied... No two days are alike! The organisation - You'll be part of the Sonepar family and share the same values! The culture - You'll be working in an international environment. The team - Our dynamic, multidisciplinary, open-minded and talented team is eager to welcome additional skills to continue to meet the challenge. 75% reimbursement of your monthly or annual transport pass. Swile Ticket restaurant card Gym exclusively reserved for the company and made available to employees free of charge. Sustainable mobility package Health insurance & Welfare Employee Savings Plan & Profit Sharing Bonus.