Analytics Engineer

LiveKit is building the infrastructure layer for the voice-driven era of computing. Our platform gives developers everything they need to build, test, deploy, scale, and observe agents in production. Founded in 2021, LiveKit powers voice AI applications for OpenAI, xAI, Salesforce, Coursera, Spotify, and thousands of others, collectively facilitating billions of calls each year.

• obsess with crafting code that is fast, reliable and practical for the problem

• are known as the go-to person for tackling tough technical problems

• work hard and can build and ship fast

• can clearly explain complex technical concepts to others

• are a fast learner, frequently picking up new languages and tools

The best way to impress us is with thoughtful Issues and/or PRs on our Github repos 😊

As our first data hire, you'll establish the foundation of LiveKit's analytics practice. You'll translate business concepts into robust data models, create actionable KPIs, and enable data-driven decision making across a fast-growing organization. This role requires balancing pragmatic short-term solutions with building for scale, working in an AI-first development environment where tooling like Claude Code and skills-based workflows are core to how we operate.

AI-First Development: You'll be expected to use AI coding assistants extensively and evolve our AI development workflows. This includes creating reusable skills, establishing quality checks, and documenting processes that work for both humans and AI agents.

Start Simple, Stay Focused: Resist the urge to over-engineer. Get core business metrics right and adopted before expanding. We value working models over perfect architectures.

Business Partnership: You'll spend significant time with stakeholders memorializing business logic and creating trusted metrics. Building relationships and business expertise is as important as technical execution.

Documentation-Driven: Everything you build needs clear documentation that serves both human users and AI systems.

Engineering Standards: This role reports into Engineering and follows eng best practices. Expect PR reviews, automated testing, and production-grade standards.

Startup Pace: Priorities shift quickly. What you're building tomorrow might differ from today. Comfort with ambiguity and rapid iteration is essential.

• 8+ years experience in analytics or analytics engineering

• Deep expertise with dbt: data modeling, testing, documentation, project architecture, and establishing best practices

• Strong experience implementing and scaling BI platforms (Lightdash, Sigma, Omni, Hex, or similar)

• Proven ability to work directly with business stakeholders to define metrics and requirements

• Experience building analytics practices in startup or high-growth environments

• Strong SQL and Python skills

• Comfortable with software engineering practices: Git workflows, CI/CD, code review, change management

• Self-directed and adaptable—able to switch between building for the long-term and pragmatic short-term solutions

• Strong communication skills for both technical and non-technical audiences

• Located in US or Canada

• Experience with Lightdash or BI-as-code platforms

• Background with AI coding agents (Claude Code, GitHub Copilot, Cursor)

• Prior experience as an early data hire (first 1-3 on the team)

• Understanding of modern data stack and lakehouse concepts

• An opportunity to build something truly impactful to the world

• Contribute to open source alongside world-class engineers

• Competitive salary and equity package

• Health, dental, and vision benefits

• Flexible vacation policy