We don't just use AI. We build with it, ship with it, and think with it. We're in the top 1% of companies applying AI effectively, not just to our products, but to how we build them. With an unlimited budget for Anthropic tokens, our engineers use AI agents to write, review, and ship production code every day. We're building toward a world where humans design systems and AI builds them, and we're already further along that path than almost anyone else.
As a Staff Software Engineer, you'll be a technical leader at the center of this transformation. You'll shape platform architecture, drive AI-powered product delivery, and raise the bar for what a small, AI-augmented engineering team can accomplish. This is a role for someone who already lives in their terminal with AI, who has strong opinions about how AI changes system design, and who wants to help define what a next-generation engineering organization looks like.
What You'll DoOwn and evolve a tool-agnostic analytics layer powering business decisions. Design and maintain scalable, well-modeled datasets using dbt, Snowflake, and a semantic layer—transforming raw data into trusted, high-quality metrics used across Product, GTM, Finance, and Operations.
Partner deeply with analysts and business stakeholders. Collaborate with Data Analysts, Product, and business leaders to define metrics, enable self-service analytics, and deliver insights that directly impact decision-making and product development.
Drive data quality, consistency, and trust at scale. Implement robust testing, monitoring, and validation frameworks to ensure data accuracy and reliability, while standardizing metric definitions across the organization.
Build data products and AI-powered analytics systems. Develop systems such as AI-driven support ticket classification and contribute to building an AI agent that can act as a Data Analyst—leveraging the semantic layer to answer business questions and generate insights.
What We're Looking ForAttributes
You already build with AI daily. You use Claude Code as a core part of your workflow, not as a novelty
You have strong opinions on how AI can enhance analytics workflows, data modeling, and decision-making
You think in systems. You connect technical decisions to customer outcomes and long-term business value
You communicate clearly and directly. You can explain complex tradeoffs to product, design, and executive stakeholders
You're energized by ambiguity and speed. You thrive in a fast-growing company where the roadmap evolves and ownership is real
You like to have fun at work. We take our craft seriously, but we don't take ourselves too seriously. We celebrate wins, crack jokes, and genuinely enjoy building together
Skills and Experience
8+ years in analytics engineering, data engineering, or related roles, including time operating at a large scale or leading cross-functional initiatives.
Deep proficiency with dbt, including building and maintaining large-scale transformation layers and reusable models.
Strong SQL skills and a background working with Snowflake or similar cloud data warehouses.
Designing and operating scalable semantic layers to provide consistent, reliable metric definitions across the organization.
Expertise in designing modular, scalable data architectures (e.g., Kimball or OBT) that balance query performance with ease of use for downstream analysts.
A history of building data quality frameworks, testing strategies, and monitoring for analytics datasets.
Building data products or internal tools while partnering with product and business teams to define metrics and drive decisions.
Expert-level grasp of software design principles and a deep understanding of multi-tenant platform architectures.
Proven track record leading high-impact analytics initiatives from concept through delivery.
Tech Stack
Frontend: Sigma, Hex
Backend: dbt, SQL, Python
Data: Snowflake
Infrastructure: Airflow
