Analytics Engineer

Warp: We're Building the Platform for Agentic Development Warp began with the vision of reimagining one of the fundamental dev tools—the terminal—to make it more usable and powerful for all developers. As AI has advanced, Warp has evolved beyond its terminal roots into the platform for Agentic Development: a workbench for dispatching agents to code, deploy, and debug production software. With over 700k active developers and revenue that grew over 44x last year, Warp is now one of the fastest growing startups in the exploding AI development space. We believe that soon developers will be “tech leads” for groups of agents; rather than opening a code editor to write code or a terminal to write commands, they will open Warp and prompt their computer to build features, fix bugs, and diagnose production issues. With its starting point as a reimagined command line, Warp is well-positioned to support agent-first workflows: It sits at the lowest level in the dev stack, has access to all of a developer’s context, and is set up for multitasking and long-running processes. In addition, Warp has state-of-the-art code editing features and built-in team knowledge sharing. It’s the right interface for the agentic future. Our mission has remained the same even as AI has advanced: to empower developers to ship better software more quickly, freeing them to focus on the creative and rewarding aspects of their work. For more information on our team and culture, we highly recommend reading our How We Work . Why this role? We’re hiring an Analytics Engineer to join Warp’s data team, reporting to Ian Wright, our Data Lead. Warp is a fast-growing AI developer tool, and our data footprint is expanding quickly—we ingest telemetry from our apps and servers, LLM conversational data, transactional production databases, GTM pipelines, and a variety of third-party sources. The data team’s job is to transform this raw data into reliable metrics and deep insights that help us understand how our product is used, how the business is growing, and where we should go next. As an Analytics Engineer, you will... This is a full-stack data role that moves across the data stack and touches all parts of Warp’s business. Your work will fall into three broad areas: Operations Define, build, and visualize core product and business metrics Design and analyze A/B experiments to measure the impact of product changes Adapt data models to support new product features, pricing models, and business initiatives Partner with GTM teams to surface product-qualified leads, measure engagement, and support billing and revenue analytics Infrastructure Build and maintain canonical data models that serve as reliable sources of truth Write production ETL to ingest new data sources and reverse-ETL to push data to downstream consumers Develop AI agents to automate pieces of the data team’s workflows Establish data quality monitoring and reliability standards Build tooling that enables self-serve analytics across the company Research Conduct deep ad-hoc analysis to understand user behavior, model business mechanics, and uncover growth opportunities Dig into questions like: How does Warp expand within companies? What is the optimal pricing structure? How do we identify potential enterprise leads? What characteristics of AI interactions drive churn? You May Be A Good Fit If... You have 4+ years of experience in an analytics-focused data role You’re highly fluent in SQL and dbt on top of a modern warehouse like BigQuery, Snowflake, or Redshift You’ve built dashboards and visualizations with BI tools like Hex, Looker, Mode, Tableau, or Metabase You care deeply about the business decisions your data informs—not just building the pipelines behind them You balance business intuition with an engineering mindset: writing efficient, scalable queries; thinking about cost and compute across the data stack; and working with version control, CI/CD, and testing You have a bias fo ... (truncated, view full listing at source)