Analytics Engineer – dbt & Metrics Architect

Carbon Data Solutions; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Generous learning stipend

Annual company offsite

Job summary

ElevenLabs is seeking an experienced Analytics Engineer to join the Data team as one of its first hires. You will own the transformation layer between raw data and business decisions, modelling data in dbt, defining certified metrics, and setting coding standards for analysts and data scientists.

Responsibilities include building a world-class metric layer, designing the KPI layer for product, finance, and company-wide topics, and partnering with Data Engineering to evolve the data warehouse.

Qualifications

• Demonstrated experience building and scaling a dbt project and metrics layer.
• Expert knowledge of dbt and advanced SQL (required); strong grasp of dimensional modelling, grain, and incremental patterns.
• Proficiency across the modern data stack: warehouse, Python, BI tools like Looker.
• Rigour around data quality: test, document, and reconcile by default.
• Strong ability to translate stakeholder requirements into generalized, well-documented models.

Responsibilities

• 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, finance, 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 data products, including data served through AI agents.

Skills

Advanced SQL

Data modeling

Stakeholder management

Analytics engineering

CI for data

Education

Bachelor's degree in a relevant field

Tools

dbt

BigQuery

Python

Looker

CI tooling

Job description

ElevenLabs is seeking an experienced Analytics Engineer to join the Data team as one of its first hires. You will own the transformation layer between raw data and business decisions, modelling data in dbt, defining certified metrics, and setting coding standards for analysts and data scientists.

Responsibilities include building a world-class metric layer, designing the KPI layer for product, finance, and company-wide topics, and partnering with Data Engineering to evolve the data warehouse.