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Staff Software Engineer

Dbtlabsinc
3 days ago
Full-time
Remote
Worldwide
Remote Engineering

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 90,000 teams every week, driving data transformations and AI use cases. 

As of February 2025, we’ve surpassed $100 million in annual recurring revenue (ARR) and serve more than 5,400 dbt Platform customers, including AstraZeneca, Sky, Nasdaq, Volvo, JetBlue, and SafetyCulture. 

We’re backed by top-tier investors including Andreessen Horowitz, Sequoia Capital, and Altimeter. At our core, we believe in empowering data practitioners:

  • Reliable, high-quality data is the fuel that propels AI-powered data engineering.

  • AI is changing data work, fast. dbt’s data control plane keeps data engineers ahead of that curve.
  • We empower engineers to deliver reliable, governed data faster, cheaper, and at scale.

dbt Labs 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.

About the Role

We are building the next foundational layer of the analytics stack: an Enterprise Context Platform that captures, stores, and exposes organizational decision memory.

As a seasoned engineer on Context Platform Systems, you will architect and build the durable memory substrate that powers agentic analytics workflows. This platform stores not just metadata, but meaning: decisions, intent, rationale, and history — and makes it safely accessible to humans, agents, and applications.

This is a greenfield, high-leverage role with company-level impact.


What You’ll Do

  • Prototype apt technical solutions and find best fits for the context engine. Architect and build the core Context Platform
  • Design schemas and primitives for Decision Memory and enterprise context
  • Own context storage systems (graph, vector, event/time-based)
  • Build read/write/query APIs used by agents, products, and external apps
  • Design permission-aware, auditable context access