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Staff Software Engineer (Metadata)

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Onsite

Staff Software Engineer (Metadata)

Fivetran

Staff Software Engineer (Metadata)

Skills

Google Cloud PlatformDockerPythonJavaC#PostgreSQLKafkaSnowflakeGraphQLDatadogData AnalysisAIAWSKubernetesAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

$162,157 – $198,877 / year

Location:

Oakland, CA, USA

Work mode:

Onsite

Published on:

18 August 2026

What they need


  • 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 be a technical leader on 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
  • As a Staff Software Engineer, you’ll contribute to the technical direction for the team
  • You’ll own the architecture of major subsystems, lead complex projects that span multiple engineers, and raise the bar for design and code quality across the team
  • You’ll spend your time on the hardest technical problems, and multiply the team through design reviews, coaching, and mentorship
  • Lead the design and delivery of complex, team-level projects across the Metadata services, coordinating development across multiple engineers
  • Independently design and develop the architecture of new subsystems, and own team-level subsystems end to end
  • Use AI tooling and agents — across development and SDLC artifacts such as TDDs, PRDs, post-mortems, and test plans
  • Review and approve technical designs, ensuring they meet a high quality bar, and identify design deficiencies before they ship
  • Drive technical initiatives across the team’s responsibility areas — discovery API, catalog, lineage, and run history
  • Set and uphold design, architecture, and coding best practices, and hold teammates accountable for code quality
  • Coach and mentor engineers, demonstrably improving the quality of code across the team
  • Write technical specs, document common components, and keep the team accountable for necessary project documentation
  • Fix and optimize critical parts of the codebase, drive incident follow-through, and advance the reliability and performance of the services you own
  • Participate periodically in the on-call rotation
  • Technologies You’ll Use:
  • Python, GraphQL, Postgres, Snowflake, Kafka, Kubernetes, Docker, AWS, GCP, Datadog- Excellent design and architecture judgment; identifies design flaws in existing systems and proposes sound solutions with clear trade-offs
  • Experience partnering with QE on test strategy and owning operational health — incidents, post-mortems, reliability, and performance
  • 8+ years of software engineering experience with a track record of leading complex, team-scope technical work to completion
  • Proficiency in a modern backend or systems language such as Python, Java, C++, or C#
  • Fluent in using AI code assistants and coding agents to generate and investigate code, and conversational AI (e.g. Claude, ChatGPT) to author, review, and synthesize SDLC artifacts — and able to model those practices for a team
  • Strong track record of raising quality through code review, coaching peers, and enforcing accepted engineering practices
  • Deep expertise designing and owning subsystems in distributed, cloud-based systems
  • Writes exemplary, well-tested code that serves as a model for others, and reliably estimates and delivers sprint to sprint
  • Hands-on experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and managing dev infrastructure
  • Demonstrated ability to set technical direction for a team and drive multi-engineer initiatives across an area of ownership
  • Experience in data processing (ETL, ELT) and/or cloud-based data platforms
  • Familiarity with the analytics engineering workflow and the dbt ecosystem
  • Experience with GraphQL APIs and high-throughput, multi-tenant data services
  • Experience architecting metadata, catalog, lineage, or discovery/search systems

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