VP DATA

Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy.

Today, Mirakl’s operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI‑powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third‑party marketplace sellers. Brands like Macy’s, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways.

Mission

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.

What You’ll Do

Lead the Data Organization

• 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.

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).

Enable AI Development & Serving

• Build a best‑in‑class AI development platform.
• Provide Data Scientists, Agent Builders, and AI Engineers with tooling for experimentation at scale, operation of robust model serving and inference, performance monitoring, and cost control.

Build Agentic Foundations

• Enable teams to develop, run, and evaluate agents at scale.
• Provide tooling for development (frameworks, integrations), execution (orchestration, tools, memory), monitoring, evaluation (metrics, testing, feedback loops), and standardize agent lifecycle, safety, and reliability.

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.

Who You Are

Background

• 10–15 years in data, AI, or platform organizations, leading high‑performing cross‑functional teams.
• Proven track record building data platforms and analytics systems that drive business decisions and power product experiences.
• Experience delivering data and analytics products such as semantic layers, metrics, and business‑facing models.
• Strong understanding of data and 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.

What Makes You Successful

• Build production‑grade platforms and organizations that scale.
• 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.
• Platform adoption and speed (AI and agent adoption, time to build, deploy, evaluate, budget efficiency).

Organization & Scope

• ~25+ people in Data (part of 75+ Data & AI organization) with squad setup.
• Data and Agentic Platform (~17): Data Eng, SRE, MLOps, Agentic Platform.
• Data Product & Analytics (~8): Analytics Eng, Data Product.
• Ownership of €3M+ annual budget.

We welcome collaborators with diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning.