Paris
Join a fast-growing AI scale-up building intelligent automation products Join an innovative and rapidly growing AI company as their Data Lead, and play a foundational role in building a modern, scalable, and reliable data infrastructure serving both internal teams and international clients. Already adopted by leading European companies, the platform leverages AI agents to transform complex operational workflows at scale. This is not just a data role. It is an opportunity to design the entire data architecture from scratch and make data a core strategic asset of the company. 🧠 About the Role: This is a foundational position within the organization. As Data Lead, you will define the architecture, tools, standards, and governance across the full data lifecycle, from ingestion to client-facing dashboards. You will operate at the intersection of: • Engineering, • Product, • Operations, • Business, • Clients Your work will directly influence product decisions, customer visibility, and executive strategy. 🛠 What You’ll Build & Own You will be responsible for: • Designing and deploying a modern data infrastructure (ETL / ELT, data warehouse architecture), • Implementing BI and visualization tools (Looker, Metabase, etc.), • Building internal and client-facing dashboards, • Structuring data quality, governance, documentation, security, and access management, • Developing real-time reporting systems for internal teams and end users, • Leveraging AI tools (LLMs, agents) to enable self-service data access and automated insights, • Acting as the key interface between engineering, product, ops, business stakeholders, and clients This is a blank-page opportunity, you define the standards. 🛠 Tech Environment Data Stack: dbt, Snowflake, BigQuery, Looker, Metabase Languages & Infrastructure: Python, SQL, Airflow Cloud: GCP / AWS AI Layer: Active use of LLMs to automate insights and data accessibility 🔍 What We’re Looking For We’re seeking a senior data professional who wants to own the entire data function, not just maintain pipelines. Must-have qualifications: • 5+ years of experience in Data Engineering, Analytics Engineering, or Data Platform roles, • Experience in SaaS, scale-up, or AI-native environments, • Strong command of modern data tools (dbt, Snowflake, BigQuery, Looker, etc.), • Proven experience managing the full data lifecycle (ingestion → transformation → reporting), • Strong focus on data clarity, reliability, and documentation, • Comfortable operating in cross-functional environments (Product, Growth, Customer Success, Ops), • Enthusiastic about leveraging LLMs to enhance data workflows and access Nice-to-have: • Experience building scalable client-facing reporting systems 🌍 Work Environment • Based in Paris (hybrid model), • High-impact role with dashboards visible to clients and executive leadership, • Product-first culture with strong ownership, • AI-native mindset and rapid execution cycles, • International client base with complex operational challenges 🚀 Why Join? • Blank-page opportunity: Build a modern data stack from the ground up with no technical debt, • Real business impact: Data drives every product, customer, and strategic decision, • Ownership: You define standards, architecture, and governance, • AI-first environment: Work at the intersection of data infrastructure and intelligent automation, • Scale-up journey: Join a high-growth tech company at a decisive stage 🧪 Recruitment Process We keep things efficient and meaningful: • 45-min vision & fit discussion with a Co-Founder, • 60-min 100-day strategy discussion (data vision + AI + infrastructure), • 30-min conversation with the CEO (values & impact), • Cross references (x2), • Final call & offer