Staff/Senior Analytics Engineer (Data Science & Analytics)

Join our Data Science & Analytics team as a Staff/Senior Analytics Engineer. In this engineering-focused role, you will own the end-to-end production of data pipelines, collaborate with cross-functional teams, and apply AI tools to enhance analysis and development. You will also establish organized data marts, drive cross-functional delivery, and raise analytical standards. Experience in analytics engineering, SQL, and the retail industry is preferred.

• Posséder et maintenir des pipelines de données de production, de la conception à la livraison.
• Collaborer étroitement avec les équipes de gestion de produit, d'ingénierie et de science des données pour expédier des fonctionnalités fiables.
• Établir des marts de données organisés pour permettre l'analyse autonome et les insights alimentés par l'IA.

• You are someone who thrives at the intersection of data and software engineering: you write production code, own the reliability of the systems you build, and drive cross-functional projects to completion without waiting to be unblocked
• Experience owning the full lifecycle of analytics features: scoping, building, shipping, and maintaining
• Hands-on experience using AI tools (LLM APIs, coding assistants, prompt engineering) to accelerate analytical work
• Experience with dbt for data transformation and Kimball Dimensional modeling: writing models, tests, and documentation as part of a production analytics engineering workflow
• 5+ years of experience in analytics engineering or a closely related role, with demonstrable delivery of production features
• Solid SQL and experience working with large-scale cloud data platforms (GCP/BigQuery preferred)
• Retail industry experience strongly preferred (store operations, inventory, merchandising, supply chain, or equivalent)
• Proven ability to work across functions: you've partnered with Engineering, Product, or Commercial teams and know how to communicate tradeoffs and drive alignment
• Familiarity with, pipeline orchestration (Airflow or similar), model monitoring, CI/CD for analytical workflows
• Experience with data visualization tools (Looker, Tableau, or similar) for communicating findings to non-technical stakeholders