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Salary: USD 170,000 - 200,000 / annual
Granola is an AI-powered notepad for people in back-to-back meetings that has evolved into a shared workspace helping teams capture, organize, and act on information. The company works with many ambitious organizations and is now seeking a Senior Analytics Engineer to build the financial and operational data infrastructure supporting the next growth phase.
In this hybrid role spanning data engineering and analytics, you will work alongside the existing data team to improve how data is ingested, modeled, and monitored across the company. You'll partner with Go-to-Market and Finance teams to transform the data foundation into actionable reporting and decision-making.
Key responsibilities include:
- Building and scaling the business data foundation, ensuring reliable data ingestion into the warehouse and availability when needed
- Developing and improving the dbt modeling layer to turn data from multiple systems into clean, intuitive datasets
- Establishing strong practices around testing, monitoring, alerting, and documentation to catch issues before they reach end users
- Partnering across teams to define core metrics, codify definitions in data models, and improve consistency across dashboards
- Creating dashboards and analyses that help leaders and operators understand what is happening, why, and what to do next
- Improving data discoverability and usability through better documentation, naming conventions, and tooling
You'll be a hands-on builder who enjoys creating and improving foundations as the company scales, comfortable bringing clarity to ambiguous business questions and making progress without perfectly defined requirements. The role values collaboration, clear communication between technical and business contexts, and the ability to translate between functional leaders' needs and technical solutions.
REQUIREMENTS:
- 8+ years of experience in 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 (ingestion, transformation, data quality, monitoring, business intelligence)
- Experience designing clean, scalable data models combining information across multiple operational systems
- Expertise building intuitive dashboards and self-service reporting in modern BI tools (Omni, Looker, Tableau)
- 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
