Staff Software Engineer

dbt Labs dbt Labs · Data AI · India · Remote · Engineering

dbt Labs is seeking a Staff Software Engineer to join their dbt Fusion team, focusing on building the next generation of data execution and connectivity infrastructure. The role involves designing and shipping core abstractions for how dbt communicates with execution systems, leveraging Rust, Go, and Arrow. This is a foundational platform role with a strong emphasis on systems programming, database internals, and open-source development.

What you'd actually do

  1. Design, build, and maintain Rust-first connectivity layers, execution APIs, and adapter scaffolding.
  2. Partner with teams building the dbt compiler, semantic layer, and runtime to evolve adapter interfaces and system boundaries.
  3. Contribute to Arrow/ADBC and other open-source specifications or implementations, strengthening the data ecosystem.
  4. Own CI, testing frameworks, profiling, error reporting surfaces, and release readiness for Fusion adapters.
  5. Debug complex interoperability and performance issues across drivers, engines, and compute domains.

Skills

Required

  • Rust
  • Go
  • C++
  • SDK design
  • Library design
  • Connector development
  • Compute integration
  • Data integration
  • Data warehouses
  • Query engines
  • Arrow
  • Columnar ecosystems
  • Execution runtimes
  • Public code review
  • Async communication
  • RFC processes
  • Debuggability
  • Reliability
  • Ownership

Nice to have

  • Arrow
  • ADBC
  • DuckDB
  • Presto
  • DataFusion
  • Spark
  • ClickHouse
  • Adapter standards
  • Plugin standards
  • Driver contracts
  • Architectural interfaces
  • Rust async ecosystems
  • tokio
  • tower
  • tracing
  • Go concurrency practices
  • OSS governance
  • Issue triaging
  • PR review
  • Community maintainer interaction
  • Developer-experience layers
  • Scaffolding frameworks

What the JD emphasized

  • Strong programming background in Rust, Go, C++ or similar performance-oriented languages.
  • Experience designing or maintaining SDKs, libraries, connectors, or compute/data integration codebases.
  • Exposure to data warehouses, query engines, Arrow/columnar ecosystems, or execution runtimes.
  • A desire to build foundational platform components that other teams and community members rely on.
  • Comfort working in public code review loops, async-first communication, and collaborative RFC processes.
  • A mindset grounded in debuggability, reliability, and ownership in ambiguous problem spaces.