Staff Backend Engineer, Data Platform

• Own consistency across systems that each hold their own copy, under retries, reordering, and partial failure, from ingestion off upstream systems through routing each use to the right destination
• Lead canonical schema design and evolution while systems are already reading and writing through the model, covering migrations, versioning, and reference data with effective dates so past decisions stay provable
• Define the system architecture, including systems of record, ownership boundaries, replication strategy, and access control
• Design the write path where automated and human writes arrive concurrently and sometimes conflict, covering validation, permissions, and audit history complete enough to reconstruct who changed what and why
• Set the data modeling standards, and be the engineer consulted before shared entities change

The strongest signal for this role is having been accountable for a shared data model that multiple teams depended on: getting those teams to agree what a concept means, encoding that agreement in the schema, and keeping it consistent across systems that each hold their own copy, under retries, reordering, and partial failure., * Depth in asynchronous and event-driven service design, including idempotency, concurrency control, and the integration patterns that keep systems consistent

• Advanced data modeling and schema design, including temporal and audit requirements where you have to reconstruct what the system knew at a point in time
• Sound judgment on technical debt, meaning deliberate tradeoffs, a clear view of what they cost, and the discipline to know where not to compromise
• Demonstrated impact on team capability, including standards that persisted beyond your involvement and engineers whose growth you can speak to specifically
• Strong partnership with non-technical domain experts, translating what they ask for into what the data platform should actually build, and technical tradeoffs into decisions they can make
• Hands-on Python across our stack or close equivalents, including Postgres, BigQuery, GCS, and containerized services and scheduled jobs on Cloud Run

Nice to have

• Establishing data standards or architectural practice in an organization without them
• Collaborating with scientific or technical domain experts and translating their vocabulary into a data model

For all Full-Time Employees, compensation is just one component of Osmo’s total rewards approach, which is designed to support the well-being, growth, and long-term success of our team members. Depending on the role, this may include base salary or contract-based pay, along with access to health, dental, and vision coverage; a 401(k) retirement savings plan with company match; flexible paid time off and company holidays; and equity or incentive compensation for eligible roles. Actual compensation will vary based on factors such as experience, skills, location, internal equity, and other relevant business considerations. Osmo regularly reviews pay ranges and compensation structures to ensure they remain competitive, equitable, and aligned with current market data.