Data Engineering Lead

Join our team as a Tech Lead - Data Engineering, where you will be the primary architect and owner of our data platform. You will define how data is ingested, modeled, stored, transformed, and exposed across the company, with a focus on robust pipelines, clear data contracts, and reliable operation at scale. This is a hands-on role with direct responsibility for critical systems, and you will work closely with product and engineering teams to design and lead data foundations for machine-learning-powered product features.

• Assumer la responsabilité de la plateforme de données, y compris l'ingestion, le stockage, la transformation et les couches d'exposition.
• Diriger la conception de systèmes de données distribués, en veillant à une intégration propre entre les services backend, les API externes, les flux d'événements et les couches de stockage de données.
• Travailler en étroite collaboration avec les équipes produit et d'ingénierie pour concevoir et diriger les fondations de données pour les fonctionnalités de produit alimentées par l'apprentissage automatique.
• **Architectural Mindset:** Proven experience as a Tech Lead, Principal Engineer, or System Architect designing and owning complex, distributed systems.
• **Strong Software Engineering Foundations:** A software-engineer-first mindset with deep experience in Python and production-grade engineering practices. Experience with libraries such as Pandas or Polars is expected, but architectural thinking matters more than specific tools.
• **Machine Learning Exposure:** Hands-on experience working with machine learning systems and tooling (e.g. Hugging Face, feature stores, model inference pipelines, or similar), with an emphasis on enabling ML in production rather than research experimentation.
• **Database & Storage Expertise:** Advanced SQL skills and hands-on experience with modern cloud data warehouses (e.g. Snowflake or equivalent), alongside solutions for unstructured or semi-structured data.
• **ETL/ELT & Orchestration:** Experience designing and operating modern data pipelines using tools such as dbt, Airflow, or equivalent orchestration and transformation frameworks.
• **Engineering Rigor:** Deep experience with Git-based workflows, CI/CD pipelines, automated testing, and maintaining long-lived systems in production.
• **Engineering Judgement:** Demonstrated ability to make and defend trade-offs—when to model data, when not to ingest data, and how to balance correctness, performance, and cost.
• **Analytical Depth:** Ability to interrogate and analyse data directly to validate system behaviour and ensure high levels of data quality.

**Desirable**

• Experience with **Analytics-as-Code** platforms such as Looker/LookML.
• Experience building internal platforms that enable, rather than directly deliver, BI and reporting.
• Experience with automation platforms such as **n8n** for connecting operational systems.
• Experience designing systems for multimodal data (text, images, video, documents).