VP DATA

Mirakl is building a hybrid agentic company that relies on data, AI, and agentic foundations to drive its next phase of growth. We are looking for a senior leader to run the Data organization, build secure and scalable data infrastructure, and enable AI and agentic product development.

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 (hundreds 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:

Model development, testing, deployment

Experimentation at scale

Operate robust model serving / inference (trillions of tokens/year)

Ensure 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) and Monitoring

Evaluation (metrics, testing, feedback loops)

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 (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, working closely 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

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

End‑to‑end ownership: data → analytics → AI & agents platform

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.

As part of our recruitment process, Mirakl processes your personal data to review and manage your application, and where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, in English and French.

We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews.

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