Data Engineer
Join ElevenLabs as a Data Engineer to build and scale data pipelines in a dynamic AI-focused environment.
Posted by employer 1 week ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
What you'll build
- Build and scale data pipelines
- Establish best practices
- Ensure data quality
- Enable self-service data access
- Create AI agents for data questions
Must have
- Expert knowledge of dbt
- Demonstrated experience formalising and scaling data pipelines
- Proficiency with Python and SQL
- Strong infra fundamentals
AI in the day-to-day
We use AI to move faster with higher-quality results across the whole company.
Requirements
- Experience
- 3+ years
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
In this role, the Data Engineer is responsible for building and scaling data pipelines, ensuring their reliability and efficiency while enabling self-service data access for various teams. Key skills include expertise in dbt, proficiency in Python and SQL, and a solid understanding of cloud infrastructure. This position is ideal for someone with experience formalizing data processes, particularly in a fast-paced environment, and who can effectively translate complex data needs into actionable solutions. ElevenLabs fosters a high-velocity culture that emphasizes impact over titles, making it suitable for those eager to contribute meaningfully.
Joblaze insights
- Listed yesterday — first seen on Joblaze November 7, 2026. Last confirmed on ElevenLabs's careers page November 7, 2026.
- This exact title is also open at 1 other location at ElevenLabs: United Kingdom.
Quick facts
- Is the Data Engineer role remote?
- Yes — ElevenLabs lists this as a fully remote position.
- How much experience is required?
- At least 3 years of relevant experience for this Data Engineer role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: GCP, Python, SQL, Terraform, dbt.
- What seniority level is this role?
- ElevenLabs targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Data Engineer role at ElevenLabs.
From the original posting
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.
How we work
High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.
What we offer
Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.
About the role
We’re looking for an experienced Data Engineer to join our Data team. You will build and scale our data pipelines, establish best practices, ensure data quality, and enable self-service data access across teams.
Own and streamline data pipelines from ingestion to delivery, ensuring they are reliable, scalable, and efficient.
Implement and maintain dbt best practices, data standards, and quality controls.
Build self-service tooling and write clear documentation to empower cross-functional teams (Engineering, Revenue Operations, Growth, and others) to independently meet their data needs.
Create AI agents to serve data questions for others
Requirements
Demonstrated experience formalising and scaling data pipelines, ideally as one of the first or early data engineers on a growing team.
Expert knowledge of dbt (required).
Proficiency with tools across the modern data stack (Python, SQL, BI tools).
Strong infra fundamentals (Terraform or other infrastructure as code, GCP or other cloud providers)
Structured thinking; ability to simplify complex, messy data into clear structures.
Strong ability to understand varied stakeholder requirements and build generalised solutions.
Location
This role is remote and can be executed globally. If you prefer, you can work from our offices in London, Warsaw, New York.
#LI-Remote
Standard company text repeated across ElevenLabs's postings is omitted here.