Since 2016, dbt Labs has been on a mission to help analysts create and disseminate organizational knowledge. dbt Labs pioneered the practice of analytics engineering, built the primary tool in the analytics engineering toolbox, and has been fortunate enough to see a fantastic community coalesce to help push the boundaries of the analytics engineering workflow. Today there are 30,000 companies using dbt every week, 100,000 dbt Community members, and over 4,100 dbt Cloud customers. You can learn more about our values here.
As an at dbt Labs, you will be part of a team building the foundation to scale analytics across our Go-To-Market (GTM) and Product teams. You will collaborate with key stakeholders to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company’s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions.
This is a critical role for the organization and requires an individual with effective communication skills, outstanding business acumen, and the ability to work across various functional teams and internal partner teams. We are looking for individuals who are self-starters comfortable with ambiguity, demonstrate strong attention to detail, and have the ability to work in a fast-paced and ever-changing environment.
- Understand the data needs of GTM and Product teams in terms of key data models and reporting, and translate that into technical requirements.
- Own our dbt instance, defining and maintaining key data pipelines and charts that power core company-wide metrics.
- Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data.
- Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
- Build insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company.
- Build foundational data products and tools to enable self-serve analytics to scale across the company.
- Influence the future roadmap of Product and GTM teams from a data systems perspective.
- Become an expert in our GTM and Product data models and the company's data architecture.
- Worked asynchronously as part of a fully-remote, distributed team.
- Excellent communication skills to convey complex technical concepts to non-technical stakeholders.
- Have 4+ years of experience as an Analytics Engineer or similar Data Science & Analytics roles, preferably partnering with GTM and Product leads to build and report on key company-wide metrics.
- Expertise in SQL and Python to transform data into accurate, clean data models.
- Expertise in building multi-step ETL jobs through tooling like dbt and orchestrated through workflow management platforms like Prefect.
- Experience building data reporting and dashboarding in visualization tools to serve multiple cross-functional teams.
- A bias for action and urgency, not letting perfect be the enemy of the effective.
- A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even it it requires going outside the original job description.
- Experience developing and scaling a dbt project while leveraging engineering best practices (e.g. data quality tests, unit tests, etc).
- Have experience at a SaaS company
- : Commensurate based on experience
- : For employees outside the United States, dbt Labs offers a competitive benefits package
What to expect in the hiring process
At dbt Labs, we have developed strong opinions on how companies should practice analytics.
Specifically, we believe that:
- Code-based transformations offer unmatched flexibility and transparency across various “multi-player” development to power everyone in the organization to collaborate on a common language
- Data analysts should adopt similar practices and tools to software developers
- Critical analytics infrastructure should be controlled by its users as open source software
- Analytic code itself — not just analytics tools — will increasingly be open source
It turns out that a lot of other people believe this too! Today, there are 30,000 companies using dbt every week, 100,000 dbt Community members, and 4,100 companies paying for dbt Cloud. Our customers include JetBlue, Hubspot, Vodafone New Zealand, and Dunelm. dbt is synonymous with the practice of analytics engineering, defining an entire industry. We’re backed by top investors including Andreessen Horowitz, Sequoia Capital, and Altimeter.
Want to learn more about our focus on Diversity, Equity and Inclusion at dbt Labs? Check out our DEI page here.
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What We Do
At dbt Labs, we make data work. Our open-source software, dbt, enables anyone who knows SQL to engineer, document, and test data pipelines. By empowering analysts to work like and with data engineers, dbt drastically increases an organization's ability to model and serve analytics. We’ve built a community of 100,000+ people and are backed by top investors including Andreessen Horowitz and Sequoia Capital. dbt is already used and loved by thousands of companies and dbt Cloud enables this workflow at scale.
dbt Labs headquarters are in Philadelphia, Pennsylvania, but we are a distributed team and advocate for a remote-first culture. We want our people to work from the places where they are happiest, healthiest, and most inspired to do great things.
Why Work With Us
At dbt Labs, we bring our whole selves to work. We bring our interests and experiences, our cultural influences, our physical and emotional needs, our communication styles and lifestyles, our values, and our curiosity. We have built a lot of trust in each other, and we work hard to be worthy of it.
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