Analytics Engineer
About ElevenLabs
ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always.
We have expanded from voice into three main platforms:
- ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.
- ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.
- ElevenAPI gives developers access to our leading AI audio foundational models.
Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.
How we work
High-velocity
Impact not job titles
AI first
Excellence everywhere
Global team
What we offer
Innovative culture
Growth paths
Learning & development
Social travel
Annual company offsite
Co-working
About the role
We're looking for an experienced Analytics Engineer to join our Data team as one of its first hires. You will own the transformation layer between raw data and business decisions: modelling our data in dbt, defining the certified metrics the company runs on, and setting the standards that every analyst and data scientist at ElevenLabs builds.
- Drive the implementation of a world-class metric layer for the company: modelling conventions, project structure, testing, CI, and documentation.
- Design and maintain the certified KPI layer for product (activation, adoption, retention, usage), finance (billing, ARR, revenue), and company-wide topics, built to withstand audit scrutiny.
- Partner with Data Engineering on evolving the data warehouse architecture, and with stakeholders to turn ambiguous questions into trusted, reusable data products, including data served through AI agents.
Requirements
Expert knowledge of dbt and advanced SQL
Proficiency across the modern data stack
Rigour around data quality
Strong ability to understand varied stakeholder requirements,
Bonus
- Experience modelling billing, subscription and ARR data (Stripe, Salesforce) or product event data at scale.
- Experience serving data to LLM-based agents or building semantic / metrics layers consumed by AI tools.
- Experience with CI for data (Slim CI, data contracts, PII policy tags) and infrastructure-as-code for warehouse access.
Location
Skills
Who can apply
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