About the role

Analytics Engineer building trusted data models, pipelines, dashboards, and GTM workflows for Linear’s product development system. Partnering across Product, Engineering, and GTM to make data actionable.

Responsibilities

Work across Product and GTM (Marketing, Sales, Customer Success, and Finance) to turn ambiguous questions and operational needs into useful metrics, models, analyses, and workflows
Build and maintain dbt models and pipelines that create trusted views of the product, customers, and business
Design clear, maintainable data models and improve testing, documentation, performance, and reliability of the data stack
Build dashboards and self-service reporting in Metabase and Hex, and conduct deeper analysis when needed
Operationalize data through reverse ETL and partner with GTM Engineering on scoring, segmentation, automations, and internal tools
Balance fast, pragmatic answers with durable, reusable models and workflows
Leverage emerging tools, LLMs, and coding agents to accelerate development, analysis, testing, and documentation while maintaining correctness

5+ years of experience in analytics engineering, data analytics, or data engineering, ideally at a fast-moving software company
Exceptional SQL and strong hands-on experience with dbt and a modern cloud data warehouse
Track record of owning data projects end-to-end, from shaping an ambiguous problem to shipping something people rely on
Strong data modeling judgment covering grain, reusable components, interfaces, dependencies, and maintainability
Analytical judgment to determine when to answer quickly, investigate deeply, and turn complex findings into clear recommendations
Comfortable moving between technical implementation and business context
High ownership mentality: self-directed, pragmatic, and willing to challenge requests or approaches when appropriate
Strong communication skills and experience partnering directly with technical and non-technical teams
Comfortable using LLMs and coding agents in daily development workflows
Comfortable learning quickly and working across the full data lifecycle
Experience with or ability to work across Snowflake, dbt Cloud, Metabase, Hex, Hevo, Fivetran, HubSpot, Pocus, and Clay
Must be based in North America
Must be based in a US-equivalent timezone

Competitive salary and equity
Employee-friendly equity terms including early exercise in the US and extended exercise windows
Daily meal and coffee stipend on every workday
Paid co-working space or desk
Health coverage (based on country requirements)
5 weeks paid vacation, plus local statutory holidays
4 months paid parental leave
Paid month off after 4 years & every 2 years thereafter
Regular team events and off-sites
Remote-first with no required commute