Senior Backend Engineer - Databases Tempo

Accountabilities

• 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.