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:
- Code-based data transformations unlock transparency, flexibility, and collaboration
- Analysts should adopt software engineering best practices to build trusted data products
- Core analytics infrastructure should be open source and user-controlled
- Analytic code—not just tools—should be shared and community-driven
dbt is now synonymous with analytics engineering, defining the modern data stack and serving as the data control plane for enterprise teams around the world. And we’re just getting started. We’re growing fast and building a team of passionate, curious people across the globe. Learn more about what makes us special by checking out our values.
As a Senior Data Engineer at dbt Labs, you’ll take the lead 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 manage scalable, reliable data pipelines that ingest product and event data into our data stores
- Develop and maintain canonical datasets to track key product and business metrics—user growth, engagement, revenue, and more
- Architect robust, reliable systems for large volume batch data processing
- Drive decisions on data architecture, tooling, and engineering best practices
- Enhance observability and monitoring of existing workflows and processes
- Partner cross-functionally with teams across Infrastructure, Product, Marketing, Finance, and GTM to understand data needs and deliver impactful solutions
- 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
- 5+ years of experience as a data engineer, and 8+ 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
- Strong knowledge of data infrastructure and architecture design
- 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
- Experience working in a SaaS or high-growth tech environment
- Experience working with open table format (such as Apache Iceberg) data storage across regions and clouds
#LI-Remote
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:
$163,000 - $198,000 USD
- The typical starting salary range for this role in the select locations listed is:
$182,000 - $220,000 USD
- Equity Stake*
- Benefits:
- dbt Labs offers:
- Unlimited vacation (and yes, we use it!)
- Excellent healthcare
- Paid Parental Leave
- 401k matching
- Wellness stipend
- Home office stipend, and more!
- dbt Labs offers:
What to expect in the hiring process(all interviews will be conducted via Zoom):
- Interview with a Talent Acquisition Partner to align on the role and the skills and experiences we mutually value
- 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.
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