Senior Analytics Engineer

Join our Analytics Engineering team as a Senior Analytics Engineer. In this role, you will be responsible for building and iterating on our star schema, ensuring data integrity, and partnering with engineering teams. You will translate business questions into technical requirements, design and build dimensional models, and own data quality and monitoring. This position offers unlimited PTO, health benefits, 401k matching, and opportunities for learning and development.

• Concevoir et construire des modèles dimensionnels évolutifs, en traduisant des questions commerciales ambiguës en dimensions, faits et décisions de grain.
• Assurer la qualité des données et la surveillance des modèles que vous construisez, en définissant ce que signifie "correct" pour chaque modèle et en instrumentant des contrôles de qualité des données.
• Être le lien entre les données sources et les définitions commerciales, en soutenant la définition technique des mesures commerciales clés et en favorisant l'alignement lorsque les parties prenantes ne sont pas d'accord.

• Deep data modeling expertise. You have designed dimensional models from scratch and integrated them into a cohesive analytics architecture to serve your stakeholders. You understand grain, SCD types, and fact table design tradeoffs
• Production dbt experience. You understand model materialization strategies, testing, macros, and how to keep a growing project maintainable
• 5+ years of experience in analytics engineering, data engineering, or related roles
• Strong problem decomposition: you can understand the underlying problem in requests that you receive and align them with our modeling roadmap and architecture
• Strong cross-functional communication skills and the ability to influence stakeholder & business decisions
• 2+ years of experience with BI tools (Looker preferred) and an understanding of how modeling choices shape what's possible in the analytics layer
• You treat data quality as a design problem, not a cleanup task. You have built testing and monitoring into pipelines, defined SLAs or expectations with data owners, and managed the on-call/triage side of keeping data trustworthy
• You judge your work by its usability to your stakeholders over the long-term, not just by speed of delivery, underlying architecture elegance, or immediate use case
• You can handle complex modeling scenarios, such as conforming dimensions across business use cases, modeling many-to-many relationships, handling late-arriving and restated data, and keeping models usable as the source systems evolve
• You have experience with our stack (BigQuery, dbt Cloud, Looker, Amplitude, DeepNote)
• You have worked with finance or financial services data — transactions, subscriptions, revenue recognition, ledgers, or reconciliation against a system of record
• You have experience with data governance, lineage, or catalog tooling
• You're familiar with Agile process & sprint cycles
• You have experience in mobile app or product analytics