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About Us
Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data.
Together, we're delivering the data infrastructure layer that helps organizations move, transform, and trust their data - from the moment data moves, through every transformation, to the context teams and AI systems rely on.
Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions.
As we bring our teams and technology together, we're building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It's an exciting time to join us: we're creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact.
During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

Fivetran and dbt Labs is building data pipelines to power the modern data stack for thousands of companies.
We're looking for a senior 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.

Python, Rust, GraphQL, Postgres, Snowflake, Kafka, Kubernetes, Docker, AWS, GCP, Datadog

• 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

• 5+ 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

• 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