Own the data architecture for one of our products, designing, building, and continuously evolving ETL/ELT pipelines as the product and its data model change rapidly;
Support customer-facing work: data requests, POCs, and analyses that directly influence commercial outcomes;
Drive data quality and architecture decisions independently, this role requires judgment, not just execution;
Develop HTML-based dashboards and visualizations that surface the metrics and funnel visibility the product and business teams need to act;
Build and maintain data endpoints consumed by React-based product pages, stepping into front-end development when needed because you can and it moves things faster;
Bring genuine AI fluency to your workflow, not as a buzzword, but as a way of working; we’ll ask you how you’d use AI to improve what you’re building, and we expect a real answer.

5+ years in analytics engineering, data engineering, or a closely related role
with strong, proven data modeling and ETL/ELT experience;
Python is a must. You use it regularly and confidently for transformation, automation, or analysis;
Strong SQL and a solid grasp of data warehouse architecture; hands-on experience with Snowflake or dbt is a significant plus;
Senior-level independence: you can own ambiguous problems, make architecture calls, and communicate tradeoffs clearly to non-technical stakeholders;
An active and thoughtful AI user, you have a real point of view on how AI changes data work, and you back it up with how you actually operate day-to-day;
Comfortable contributing to front-end layers or working directly alongside React engineers without friction;
Strong analytical mindset
business-oriented, funnel-aware, and able to go from raw data to insight without being handed the question first;
BS in Computer Science, Statistics, Industrial Engineering, or a related quantitative field preferred.

Senior Analytics Engineer

Key skills