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Senior Data Engineer

DBT

DBT

Data Science
United States · Remote
Posted on Friday, May 31, 2024

About Us

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.

About the role:

As a Senior Data Engineer at dbt Labs, you will take the lead in building and owning data infrastructure (e.g. infrastructure, pipelines, data products). This data ecosystem is crucial for powering analyses, guiding business decisions, accelerating growth, and driving efficiency across business operations. This team combines strategic, operational, and problem-solving skills with a pragmatic sense of how to get things done and drive change across the organization.

In this role, you can expect to:

  • Design, build and manage our data pipelines, ensuring all user and product event data is seamlessly integrated into our data warehouse.
  • Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
  • Work collaboratively with various teams, including Infrastructure, Product, Marketing, Finance, and GTM to understand their data needs and provide solutions.
  • Implement robust and fault-tolerant systems for data ingestion and processing.
  • Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to the table.
  • Ensure the security, integrity, and compliance of data according to industry and company standards.

You are a good fit if you have:

  • Worked asynchronously as part of a fully-remote, distributed team.
  • Have 5+ years of experience as a data engineer and 8+ years of any software engineering experience (including data engineering).
  • Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
  • Strong data infrastructure and data architecture skills.
  • Expertise with any of ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.
  • Solid understanding of Spark and ability to write, debug and optimize Spark code.
  • 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.

You'll have an edge if you have:

  • Experience developing and scaling a dbt project while leveraging engineering best practices (e.g. data quality tests, unit tests, etc)
  • Master’s degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Math).
  • Have experience at a SaaS company.

Compensation & Benefits

  • Salary: $180,000 - $200,000 USD
  • Equity Stake
  • Benefits: In the US, dbt Labs offers unlimited vacation (and yes we use it!), 401k w/3% guaranteed contribution, excellent healthcare, paid parental leave, wellness stipend and a home office stipend. For employees outside the United States, dbt Labs offers a competitive benefits package
  • Benefits - dbt Labs offers:
    • Unlimited vacation (and yes we use it!)
    • 401k w/3% guaranteed contribution
    • Excellent healthcare
    • Paid Parental Leave
    • Wellness stipend
    • Home office stipend, and more!

*Equity or comparable benefits may be offered depending on the legal limitations

What to expect in the hiring process (all video interviews unless accommodations are needed):

  1. Interview with Talent Acquisition Partner
  2. Interview with Hiring Manager
  3. Team Interviews

Who we are

At dbt Labs, we have developed strong opinions on how companies should practice analytics.

Specifically, we believe that:

  • Code, not graphical user interfaces, is the best abstraction to express complex analytic logic
  • 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.

dbt Labs is an equal opportunity employer. We're committed to building an inclusive team that welcomes a diversity of perspectives, people, and backgrounds regardless of race, color, national origin, gender, sexual orientation, age, religion, disability, citizenship, veteran status, or any other protected status. We feel strongly that whether or not your experience exactly fits the job description, your passion and skills will stand out and set you apart even if your career has taken some twists and turns. If you are on the fence about whether you meet our requirements, we encourage you to apply anyway! Please reach out to us directly at recruiting@dbtlabs.com if you need assistance or an accommodation.

Want to learn more about our focus on Diversity, Equity and Inclusion at dbt Labs? Check out our DEI page here.

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.