Senior Analytics Engineer

Granola•San Francisco, CA

1d•$170,000 - $200,000•Hybrid

About The Position

We are looking for a Senior Analytics Engineer to help us build the data foundation Granola relies on to run the business. This is a hybrid role spanning data engineering and analytics. You’ll work alongside our existing data team to improve how data is ingested, modeled and monitored across the entire company, while also partnering with our Go-to-Market and Finance teams to turn that foundation into better reporting and decision-making.

Requirements

8+ years of experience across analytics engineering, data engineering, business intelligence, analytics or similar roles.
Expert SQL skills and substantial hands-on experience building and scaling production data models in dbt.
Strong understanding of the modern data stack, including ingestion, transformation, data quality, monitoring and business intelligence.
Experience designing clean, scalable data models that combine information across multiple operational systems.
Expertise in building intuitive dashboards and self-service reporting in modern BI tools such as Omni, Looker or Tableau.
A track record of tackling ambiguous business questions through to structured analysis, clear conclusions and recommended actions.
Skilled at partnering directly with functional leaders and translating between business problems and technical requirements.
Hands-on builder who enjoys creating, and improving, foundations as the company scales.
Creative problem solver who can bring clarity to ambiguity and make progress without perfectly defined requirements.
Collaborative and low ego. You raise the quality of the people and work around you without needing to own everything yourself.
Clear, concise communicator who can make complicated analysis understandable and move comfortably between technical work and business partnership.

Responsibilities

Help build and scale our business data foundation. Work alongside our existing data team to make sure the data we rely on lands reliably in our warehouse and is available when the business needs it.
Build data models that reflect how Granola operates. Develop and improve our dbt modeling layer, turning data from across our systems into clean, intuitive datasets that people can confidently build on.
Improve the quality and reliability of our data. Establish strong practices around testing, monitoring, alerting and documentation so issues are identified before they reach end users.
Create trusted definitions for our core metrics. Partner with teams across Granola to define the metrics that matter, codify those definitions in our data models and improve consistency across dashboards and tools.
Build dashboards that deliver actionable analysis. Turn business questions into clear analyses, dashboards and recommendations that help leaders and operators understand what is happening, why it is happening and what to do next.
Make data easier to discover and use. Improve documentation, naming and tooling so people understand what data exists, which sources are authoritative and how different entities and systems connect.