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.
#J-18808-Ljbffr