Analytics Engineer, Data

Thank you for considering Tailscale . If this job description resonates with you, please apply. Frequently cited statistics show that people who identify with historically marginalized groups are likely to apply to jobs only if they meet 100% of the qualifications. We encourage you to help us break that statistic! About Tailscale Tailscale is making safe connection effortless by delivering software that makes it easy to securely interconnect people and their devices, no matter where they are.

From hobbyists to multinational corporations, teams of every size use Tailscale each day to protect their networks, share access to internal tools, and more. We're building a future for the Internet that's easy, sensible, and safe, like it used to be. Founded in 2019 and fully distributed, we're backed by Accel, CRV, Insight, Heavybit, and Uncork Capital.

About the Role We are looking for an Analytics Engineer who thrives in high-complexity environments—someone excited to bring clarity to chaos, untangle complex models, and lay down the foundation for scalable solutions. This is a hands-on, high-impact role for someone who isn’t afraid to address manual processes, viewing them as opportunities to build scalable solutions that drive meaningful impact.

You’ll work closely with stakeholders across the company to build reliable, trusted data models that support reporting, analysis, and decision-making. Key Responsibilities Dive into complex systems and manual workflows to develop an understanding of our tools and constraints. Thoughtfully design and maintain clean, scalable, production-grade dbt models (e.g., ARR, revenue recognition). Work across the full data pipeline, from ingestion to transformation to visualization.

Take a pragmatic approach to system challenges, balancing quick fixes with thoughtful long-term design. Collaborate with Finance, Engineering, Sales, and other teams across the company to understand data needs and deliver timely, practical solutions. What We Are Looking For Experience designing and maintaining production-grade data models and pipelines. Deep understanding of modern data modeling principles and best practices. Strong SQL skills and confidence working with complex datasets and schemas.

High attention to detail, with high standards for data accuracy and validation. Flexibility and resourcefulness in navigating manual tasks or imperfect systems. Passion for clean code, scalable architecture, and incrementally reducing complexity over time. Ab