Senior Backend Engineer - Databases Tempo

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Backend Engineer - Databases Tempo based in Canada. Join a remote-first engineering team building and scaling a distributed tracing platform that helps organizations understand application performance and troubleshoot complex systems. As a Senior Backend Engineer, you will shape the technical direction of core backend components, from data ingestion and storage to query execution and metrics generation. You will lead significant engineering initiatives focused on reliability, scalability, operational excellence, and performance. Your work will help evolve the platform into a foundation for advanced observability products and AI-powered workflows. Collaborating with product managers and engineers across teams, you will deliver robust APIs and capabilities for both human users and automated agents. This role offers substantial technical ownership, opportunities to mentor other engineers, and the chance to contribute to an open-source project in a globally distributed environment.

Lead complex, multi-month engineering projects from problem definition and technical design through implementation, rollout, and ongoing operations. Own and improve key backend components across data ingestion, storage, query processing, and metrics generation. Develop and maintain scalable APIs that support observability products, external integrations, and AI-powered assistants, emphasizing structured, predictable, and discoverable interfaces. Produce technical design documents, participate in architecture reviews, communicate engineering decisions, and balance performance, cost, maintainability, and complexity. Improve production reliability and operational efficiency by defining and tracking service-level objectives (SLOs), reducing recurring incidents, automating operational tasks, and streamlining deployments. Optimize query performance, ingestion throughput, storage efficiency, and support for long-range queries and increasingly demanding workloads. Help scale multi-tenant infrastructure through autoscaling, customer limits, safe rollouts, and operational tooling that supports growth without proportionally increasing maintenance overhead. Partner with product managers and adjacent engineering teams to understand their needs and deliver platform capabilities that unblock downstream products and workflows. Mentor junior and mid-level engineers through code reviews, design feedback, technical collaboration, and pairing. Participate in on-call rotations, incident response, and post-incident reviews, using lessons learned to improve system reliability. Contribute to open-source development by reviewing community contributions, sharing improvements, and engaging with the wider developer community. Use AI-assisted development tools where appropriate to support prototyping, testing, refactoring, documentation, and incident follow-up while maintaining high engineering and security standards. Requirements Demonstrated experience delivering complex, multi-month software engineering projects, including technical design, implementation, deployment, and production support. Strong hands-on experience building and operating distributed data systems in production, such as ingestion pipelines, storage engines, query execution systems, or comparable infrastructure. Strong software engineering fundamentals, with the ability to write clean, maintainable, reliable, and performant code. Solid experience with Go, or substantial systems programming experience in languages such as Rust, C, or C++ and the ability to develop proficiency in Go. Experience operating production services, participating in on-call rotations, troubleshooting incidents, improving service reliability, and reducing operational toil. A practical, customer-focused approach to engineering, including breaking complex problems into manageable deliverables, gathering feedback, and iterating on solutions. Strong written and verbal communication skills, including the ability to document technical decisions and collaborate effectively in an asynchronous, remote-first environment. Ability to work across teams, influence technical direction, provide constructive feedback, and help other engineers grow. Additional experience that would be an advantage: Experience with distributed tracing, OpenTelemetry, or large-scale observability platforms. Experience designing query languages, SQL- or TraceQL-like engines, or APIs consumed by other services and automated agents. Familiarity with columnar storage formats such as Parquet or specialized storage formats for analytical workloads. Experience operating large-scale, multi-tenant SaaS infrastructure across multiple cells on Kubernetes. Experience building systems for AI or large language model consumers, including structured APIs, metadata discovery, deterministic responses, and evaluation frameworks. Open-source contributions or project maintainership, with an interest in collaborating with developer communities. Previous experience using or supporting observability tools such as Grafana, Prometheus, Loki, or Tempo in production or personal projects. Experience working with globally distributed teams in a fully remote environment. Benefits Compensation: Annual on-target earnings (OTE) and base compensation range of CAD $164,490–$197,389 for Canada. Actual compensation depends on the candidate’s level, experience, skills, and assessment during the hiring process. Equity: Restricted Stock Units (RSUs), providing an ownership stake and aligning employees with the organization’s long-term performance. Remote work: A remote-first working environment designed to support collaboration across countries and time zones. Annual leave: A global annual leave policy of 30 days per year, including three designated company shutdown days, subject to applicable local legislation. Professional development: Opportunities to take ownership of high-impact technical projects, develop engineering leadership skills, and progress professionally. AI-assisted development: Access to modern AI coding assistants and leading models, supported by a company-funded usage budget and applicable security guidelines. Collaborative culture: An environment emphasizing autonomy, transparent communication, trust, open-source values, and shared ownership of outcomes. Global onboarding: In-person onboarding intended to help new team members connect with colleagues and understand the organization and its working practices. Inclusive workplace: A commitment to equal opportunity, diversity, and a respectful working environment. Healthcare and other benefits: Specific healthcare coverage, retirement contributions, and additional country-specific benefits were not detailed in the supplied description and should be confirmed during recruitment.