Audio Software Engineer On Call Jobs in Toronto, ON

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 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.

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

• 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

• 8+ years of software engineering experience with a track record of leading complex, team-scope technical work to completion
• Deep expertise designing and owning subsystems in distributed, cloud-based systems
• Demonstrated ability to set technical direction for a team and drive multi-engineer initiatives across an area of ownership
• Excellent design and architecture judgment; identifies design flaws in existing systems and proposes sound solutions with clear trade-offs
• Writes exemplary, well-tested code that serves as a model for others, and reliably estimates and delivers sprint to sprint
• Strong track record of raising quality through code review, coaching peers, and enforcing accepted engineering practices
• Experience partnering with QE on test strategy and owning operational health - incidents, post-mortems, reliability, and performance
• 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), containerization (Docker, Kubernetes), and managing dev infrastructure
• 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

• Experience in data processing (ETL, ELT) and/or cloud-based data platforms
• Experience architecting 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