Data Engineer

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.

The Role

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.

Responsibilities

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

Qualifications

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 commen