Analytics Engineer

Linear

1d•Remote

About The Position

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. The Data team works across Linear, supporting Product, Engineering, and GTM. We own our data pipelines, warehouse, dashboards, analysis, and integrations with third-party tools. As a small team, we focus on building systems that make data accessible and useful across Linear. We’re looking for someone who wants to help shape how we architect, build, and use data as we grow.

Requirements

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: you think clearly about grain, reusable components, interfaces, dependencies, and maintainability without relying on a single prescribed methodology
Analytical judgment: you know when to answer quickly, when to investigate deeply, and how to turn complex findings into a clear recommendation
Comfortable moving between technical implementation and business context, from debugging a data model to understanding product adoption or sales efficiency
High ownership mentality: self-directed, pragmatic, and willing to challenge a request or approach when something does not make sense
Strong communication skills and experience partnering directly with both technical and non-technical teams
Comfortable using LLMs and coding agents as part of your day-to-day development workflow

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 our product, customers, and business
Design clear, maintainable data models and improve the testing, documentation, performance, and reliability of our data stack
Build dashboards and self-service reporting in Metabase and Hex, and dig deeper when the answer requires more than a chart
Operationalize data through reverse ETL and partner with GTM Engineering on the scoring, segmentation, automations, and internal tools that help our teams scale
Balance fast, pragmatic answers with durable solutions, recognizing when a one-off request should become a reusable model or workflow
Find ways to leverage emerging tools, LLMs, and coding agents to accelerate development, analysis, testing, and documentation while maintaining a high bar for correctness

Benefits

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