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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # VP DATA - **Company:** Mirakl - **Location:** Paris, France - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Data Infrastructure, Data Systems, Large Language Models, Data Layers, Data Analytics, Data Management, Machine Learning Operations - **Published:** June 29, 2026 - **Apply:** https://fr.indeed.com/viewjob?jk=4c2493541227b51f ## About the Role * 10-15 years in data, AI, or platform organizations, leading high-performing cross-functional teams (platform, analytics, AI) * Proven track record building data platforms and analytics systems that drive business decisions and power product experiences * Experience delivering data and analytics products (semantic layers, metrics, business-facing models) * Strong understanding of data + AI ecosystems (analytics, LLMs, agents) and their business impact * Experience operating production systems in cloud environments, in close collaboration with MLOps and AI/agent teams ## Description Lead and scale Mirakl's Data organization to build the Data, AI, and Agentic Foundations leading Mirakl next phase of growth. Mirakl is evolving into a hybrid agentic company-internally through an agent-led organization, and externally through proprietary AI models and agentic-native products. Operating at thousands of TBs of data and trillions of tokens annually, this role ensures secure, high-quality data, production-grade AI development, and scalable model serving-enabling teams to build and operate AI systems and agents at scale., * Scale and manage Data teams across platform, analytics, and AI foundations * Define and execute the Data, AI, and Agentic Foundations strategy * Own a €3M+ budget (infra, tooling, scaling) * Drive alignment across AI, Product, Engineering, and Business * Ensure execution, prioritization, and delivery at scale 2. Build Data Foundations * Deliver a scalable, secure, governed data platform (100s of TBs) Structure data raw silver * gold for analytics and AI * Ensure data quality, reliability, observability, and security * Align data models with core business domains (revenue, ops, product) 3. Enable AI Development & Serving * Build a best-in-class AI development platform * Provide Data Scientists, Agent Builders, and AI Engineers with tooling for: * + Model development, testing, deployment + Experimentation at scale * Operate robust model serving / inference (trillions of tokens/year) * Ensure performance, monitoring, and cost control, * Enable teams to develop, run, and evaluate agents at scale * Provide tooling for: * + Development (frameworks, integrations) + Execution (orchestration, tools, memory) and Monitoring + Evaluation (metrics, testing, feedback loops) * Standardize agent lifecycle, safety, and reliability 5. Power Analytics & Agentic Products * Deliver analytics for internal and product use cases * Build and scale analytics agents (internal & in-product) * Build data, semantic, and context layers that are consistent, reusable, and agent-ready, * Connect data, AI development, and serving into one system * Balance performance, cost, security, and business impact * Drive execution with high reliability and quality standards * Operate with a platform mindset and product intuition * AI-native, hands-on with emerging paradigms like agentic coding * Drive transformation, upskilling teams and embedding new practices Success Metrics * Business impact (product value, productivity, efficiency) * Data quality, reliability, and security * Model serving performance (latency, cost, scalability) * Platform adoption & speed (AI & agent adoption, time to build, deploy, and evaluate models and agents, budget efficiency) Organization & Scope * ~25+ people in Data (part of 75+ Data & AI org) with squad setup * Data & Agentic Platform (~17): Data Eng, SRE, MLOps, Agentic Platform * Data Product & Analytics (~8): Analytics Eng, Data Product * Data & Agentic Platform End-to-end ownership: data analytics * AI & agents platform * Ownership of €3M+ annual budget ## Related Videos - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [How to govern Vibe Coding for the Enterprise](https://www.wearedevelopers.com/videos/100290-how-to-govern-vibe-coding-for-the-enterprise) ## Related Articles - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)