dbt Labs
Data Engineer
Job Summary
The Data Engineer at dbt Labs is responsible for designing, building, and maintaining scalable data pipelines and core components of the company's data ecosystem. The role involves ensuring data quality, improving system performance, and collaborating with cross-functional teams to meet data requirements. Candidates should have expertise in SQL and Python, with experience in data engineering and modern orchestration tools. The position offers opportunities to impact analytical and operational data infrastructure within a fast-growing, innovative company.
Required Skills
Benefits
Job Description
About Us
dbt Labs is the pioneer of analytics engineering, helping data teams transform raw data into reliable, actionable insights. Since 2016, we’ve grown from an open source project into the leading analytics engineering platform, now used by over 50,000 teams every week.
As of February 2025, we’ve surpassed $100 million in annual recurring revenue (ARR) and serve more than 5,400 dbt Cloud customers, including JetBlue, HubSpot, Vodafone New Zealand, and Dunelm. We’re backed by top-tier investors including Andreessen Horowitz, Sequoia Capital, and Altimeter. At our core, we believe in empowering data practitioners:
As a Data Engineer at dbt Labs, you'll assist in designing, building, and owning core components of our data ecosystem—from infrastructure to pipelines to data products. This data foundation is essential for enabling analytics, accelerating growth, and improving operational efficiency across the business. You’ll be part of a tight-knit, strategic team that combines strong technical execution with a bias for impact and cross-functional influence.
This is a unique opportunity to join a team involved in using dbt Labs products daily to build the company's internal data capabilities. This group is responsible for building and maintaining foundational data infrastructure that powers critical business decisions across the company. With executive visibility and deep cross-functional impact, the work you do here will directly influence the trajectory of our growth. If you're excited by the challenge of building from the ground up, solving complex technical problems while utilizing cutting edge technology, and driving business strategy through data, this is your chance to make a lasting mark.
In this role, you can expect to:
- Design, build, and maintain reliable, scalable data pipelines using dbt to support analytics and operational use cases.
- Implement and enforce standards that ensure high data quality, consistency, and reliability across our internal data ecosystem.
- Optimize query performance, manage compute costs, and ensure low-latency data access for downstream users.
- Continuously evaluate and enhance existing systems, proactively identifying and resolving technical debt and bottlenecks.
- Collaborate with analysts, business stakeholders, and engineers to understand data requirements and deliver relevant and sustainable solutions.
- Build automation into data workflows to reduce manual overhead and improve data freshness, lineage tracking, and monitoring.
- Provide product feedback by “dogfooding” new data infrastructure and AI technology
You’re a great fit if you have:
- Are an expert in SQL and Python
- 2+ years of experience as a data engineer, and 4+ years of total experience in software engineering (including data engineering roles)
- Proficiency in at least one additional core Data Engineering language such as Scala, Java or Rust
- Hands-on experience with modern orchestration tools like Airflow, Dagster, or Prefect
- A bias for action—able to stay focused and prioritize effectively
You’ll stand out if you have:
- Experience developing and scaling dbt projects
- Have worked in a SaaS or high-growth tech environment
- Working knowledge of open table formats (such as Apache Iceberg)
Compensation:
We offer competitive compensation packages commensurate with experience, including salary, equity, and where applicable, performance-based pay. Our Talent Acquisition Team can answer questions around dbt Lab’s total rewards during your interview process. In select locations (including Boston, Chicago, Denver, Los Angeles, Philadelphia, New York City, San Francisco, Washington, DC, and Seattle), an alternate range may apply, as specified below.
- The typical starting salary range for this role is:
- $118,000 - $143,100
- The typical starting salary range for this role in the select locations listed is:
- $131,000 - $159,000
Benefits:
- Unlimited vacation time with a culture that actively encourages time off
- 401k plan with 3% guaranteed company contribution
- Comprehensive healthcare coverage
- Generous paid parental leave
- Flexible stipends for:
- Health & Wellness
- Home Office Setup
- Cell Phone & Internet
- Learning & Development
- Office Space
Remote Hiring Process
- Interview with a Talent Acquisition Partner
- Interview with Hiring Manager
- White boarding session with a member of the data team
- White boarding session with a cross functional stakeholder
- Final wrap up/ values discussion with Data Leader
dbt Labs is an equal opportunity employer, committed to building an inclusive team that welcomes diverse perspectives, backgrounds, and experiences. Even if your experience doesn’t perfectly align with the job description, we encourage you to apply—we value potential just as much as a perfect resume.
Want to learn more about our focus on Diversity, Equity and Inclusion at dbt Labs? Check out our DEI page.
dbt Labs reserves the right to amend or withdraw the posting at any time. For employees outside the United States, dbt Labs offers a competitive benefits package. Equity or comparable benefits may be offered depending on the legal or country limitations.
dbt Labs
dbt Labs makes data transformation easy for modern data teams. Build, test, and document reliable analytics in the cloud with dbt Labs..
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