This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Backend Engineer - Databases - Analytics based in the United States.
This role offers the opportunity to build the database foundation of a next-generation, AI-native data intelligence platform. You will design and operate distributed storage and query systems capable of supporting both analytical workloads and freshly ingested data at scale. Working within a highly autonomous team, you will contribute to architecture, ingestion, query planning, distributed execution, data formats, and multi-tenant SaaS infrastructure. You will also help create reliable interfaces that enable AI agents and internal applications to retrieve governed enterprise data efficiently. The environment values rapid experimentation, pragmatic engineering decisions, ownership, and close collaboration across product and infrastructure teams. This is an early-stage opportunity with significant scope to influence technical direction as the platform evolves toward production.
Accountabilities:
- Design, implement, test, and operate one or more core components of the database, including ingestion, query planning, distributed query execution, data formats, and storage formats.
- Help architect and build a scalable, multi-tenant SaaS database foundation, including tenant isolation, usage tracking, quotas, audit logging, background jobs, and reliable service boundaries.
- Develop APIs and database interfaces that enable AI agents, MCP tools, command-line interfaces, and internal applications to retrieve enterprise data quickly and reliably.
- Make pragmatic architectural and engineering tradeoffs between rapid experimentation and long-term reliability as the platform progresses from prototype to production.
- Instrument database services with metrics, logs, traces, alerts, and dashboards to monitor system behavior and improve reliability.
- Contribute to technical direction across architecture, service boundaries, storage technologies, API contracts, deployment patterns, and engineering practices.
- Work closely with product and infrastructure teams to translate evolving requirements into scalable and maintainable technical solutions.
- Take end-to-end ownership of database solutions, ensuring they are reliable, maintainable, scalable, and aligned with real user workflows.
- Communicate effectively across a dynamic, distributed engineering environment and contribute ideas and technical expertise across teams.
- Iterate quickly by developing prototypes, gathering feedback, validating assumptions, and refining solutions based on real-world usage.
Requirements:
- Strong experience building production-grade, user-facing software systems and solving complex engineering problems with a high degree of autonomy.
- Proven ability to make sound technical and architectural decisions with minimal supervision in ambiguous or rapidly evolving environments.
- Experience with distributed systems, data catalogs, table formats, query engines, or related data infrastructure technologies.
- Strong proficiency in a programming language such as Go, C++, or Rust.
- Proven track record of delivering software that has reached production and is actively used by customers or internal users.
- Practical familiarity with AI technologies and frameworks, with a focus on building reliable solutions that deliver real-world value.
- Experience working in cloud-native environments such as AWS, GCP, or Azure.
- Experience using observability tools to understand, troubleshoot, and improve system behavior.
- Ability to rapidly prototype, validate ideas, incorporate feedback, and iterate toward production-ready solutions.
- Strong ownership and initiative, with the ability to define scope, navigate ambiguity, and drive projects toward meaningful outcomes.
- Excellent communication and collaboration skills, with a solutions-oriented approach and openness to feedback.
- Experience building distributed query engines is a plus.
- Experience developing data warehouses, data lakes, or tools for data engineering is advantageous.
Benefits:
- Base compensation range of $164,490–$197,389 CAD for roles based in Canada, with actual compensation determined by level, experience, and skillset.
- Restricted Stock Units (RSUs) providing team members with ownership in the organization’s success.
- 100% remote work environment with a globally distributed team.
- Flexible, primarily asynchronous working culture with a strong emphasis on written communication.
- Global annual leave policy providing 30 days of leave per year, including 3 Grafana Shutdown Days, subject to local legislation.
- Career growth and development opportunities within a scaling organization.
- High degree of autonomy, trust, and ownership in technical decision-making.
- Transparent communication and approachable leadership.
- Opportunities to work on meaningful, innovative projects in an open-source-inspired environment.
- In-person onboarding to help new team members build connections and understand the organization and its ways of working.
- Collaborative culture focused on diverse perspectives, creativity, and continuous improvement.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1
