Senior Analytics Engineer (Commercial)

Join our Commercial Strategy & Analytics team as a Senior Analytics Engineer. In this hands-on role, you'll build data models that drive our business growth, document reporting processes, and create analytical models for upsell and account scoring. You'll set the roadmap, maintain core data, and collaborate with stakeholders across Sales, Marketing, and Finance. This position offers a competitive salary, generous benefits, and opportunities for professional development.

• Construire des modèles de données qui alimentent la mesure, la compréhension et la croissance de l'entreprise.
• Documenter comment rendre compte des métriques clés afin que chaque équipe obtienne la même réponse.
• Développer des modèles analytiques pour l'upsell, le potentiel de whitespace, l'adéquation au profil idéal (ICP) et le scoring des comptes.

• Expert-level SQL and solid Python, both second nature for ad-hoc discovery, data workflows, and automation
• Experience building analytical models for GTM teams, such as account scoring, ICP, propensity, or whitespace analysis
• 8+ years in data or analytics roles, with 3+ in analytics engineering, ideally at a fast-paced, data-driven company
• End-to-end ownership of production data models in Snowflake (or a similar enterprise warehouse), including the trade-off calls between completeness, performance, and speed
• Deep, hands-on expertise in data modeling — from raw source data to models people actually want to build on
• A leader's instinct for ambiguity — you set your own direction, know what good looks like, and build it from scratch
• Experience inheriting, maintaining, and improving data models and ETL/ELT pipelines built by other people, adapting comfortably to different styles and existing constraints
• The instinct to break big projects into clean, well-scoped pieces, while juggling conflicting priorities
• Genuine curiosity about the business behind the data — you'll pick up our booking definitions, sales motions, and product portfolio quickly, because the right model starts with the right question
• Fluency with our stack — Fivetran, dbt, and Snowflake — and experience building semantic layers, whether in dbt or Snowflake's semantic tables
• Excellent communication — you can translate a business question into a data model without losing anyone along the way
• Experience applying software engineering practices to analytics: Git, code review, CI/CD, and automated testing