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Location
In office (Bengaluru)
Seniority
Staff · 10+ years exp

First seen by Alion on Nov 11, 2026.

Overview
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dbt Labs is the company behind dbt, the leading analytics engineering platform that enables data teams to transform, test, and document data directly in the warehouse using software engineering best practices. Trusted by thousands of organizations, dbt helps analysts and data engineers build reliable, version-controlled data models that power analytics, reporting, and decision-making. By bringing modularity, testing, and collaboration to the analytics workflow, dbt Labs makes data more trustworthy, scalable, and easier to work with across the entire organization.

Fivetran and dbt Labs are building data pipelines to power the modern data stack for thousands of companies. We're looking for a staff software engineer to join our Metadata team, which owns the metadata layer of the dbt platform: the discovery API, catalog, lineage, and run history services that let customers understand, trust, and act on what their data is doing. You'll own the design and delivery of features end to end, working across high-throughput APIs and data models to make them faster, more reliable, and more capable. You'll write and review designs, raise the quality bar in code review, use the latest AI tools, and collaborate closely with product and QE to deliver work that scales.


Responsibilities:

  • Design and implement features and performance improvements across the metadata team's services, discovery API, catalog, lineage, and run history.
  • Develop, maintain, and test high-quality, maintainable code, and optimize critical paths for performance.
  • Write technical designs for feature-level work, actively seek feedback, and clearly explain the trade-offs of your decisions.
  • Participate in and review technical designs and pull requests, providing constructive feedback to the team.
  • Improve test coverage with comprehensive unit tests and refactor code to drive down tech debt.
  • Troubleshoot and debug production issues, and follow up on incidents with post-mortems and mitigation plans.
  • Break features into tasks, structure and execute your own project plans, and contribute to sprint and feature planning.
  • Collaborate with product managers, QE, customer support, and peers to deliver the best product with high quality, performance, and scalability.
  • Participate periodically in the on-call rotation, and be mindful of security throughout your work.
  • Use AI tooling, IDE assistants like GitHub Copilot, coding agents like Claude Code, and conversational AI to accelerate development and to author and review SDLC artifacts such as TDDs, PRDs, post-mortems, and test plans.


Requirements:

  • Technologies You'll Use: Python, Rust, GraphQL, Postgres, Snowflake, Kafka, Kubernetes, Docker, AWS, GCP, and Datadog.
  • 10+ years of experience in the software industry with a passion for solving complex software engineering problems, including designing and building backend services and reusable components from the ground up.
  • Experience working with distributed systems and cloud computing concepts.
  • Demonstrated ability to write well-structured, performant, and well-tested code.
  • Ability to independently lead feature-level software and design work that satisfies project requirements and to clearly explain design trade-offs.
  • Can identify design flaws in existing systems and propose improvements.
  • Experience with code reviews, design, troubleshooting, and testing.
  • Proficiency in a modern backend or systems language such as Python, Java, C++, or C#.
  • Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Experience with continuous integration tooling such as BuildKite and familiarity with observability tools like Datadog or Grafana is a plus.
  • Fluent in using AI code assistants and coding agents to generate and investigate code and conversational AI (e. g., Claude, ChatGPT) to research, author, review, and synthesize SDLC artifacts.


Bonus Skills:

  • Experience in data processing (ETL, ELT) and/or cloud-based data platforms.
  • Experience building or working with metadata, catalog, lineage, or discovery/search systems.
  • Experience with GraphQL APIs and high-throughput, multi-tenant data services.
  • Familiarity with the analytics engineering workflow and the dbt ecosystem.

Skills

AWS, Azure, C#, C++, Docker, GCP, Java, Kubernetes, Python

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