Staff Database Engineer

About the role

Owner is the AI-native system local business owners use to succeed, starting with restaurants. This role owns the foundational data infrastructure that powers Owner itself, ensuring product teams can store and access data effectively at scale. You will be the default expert for "which database should this live in?" and "will this access pattern hold up?" across the engineering organization. You will lead large-scale migrations and build the platform primitives that hundreds of product engineers rely on every day. This is a hands-on, software-engineer-first role focused on driving the largest, load-bearing changes to our data infrastructure. Using Owner should feel like having a team of great operators, engineers, and marketers working for you.

Key facts

What you'll do

Lead the migration of product workloads from existing stores to more appropriate data platforms while minimizing risk and downtime.

Give product engineers a clear home for data architecture decisions by defining and evangelizing where each data domain should live.

Build reusable primitives such as data-sync utilities, ORM best practices, and access-pattern, schema, and index review checklists.

Expand the product-data platform over time into caching, search, and event streaming to support new access patterns and performance needs.

Partner with Product Engineering Teams to translate business requirements into scalable data models and access patterns.

Collaborate closely with Platform and Infrastructure Teams to align data-layer changes with system-wide reliability and performance goals.

Drive zero-downtime migrations on large, live tables using careful planning, tooling, and phased rollout strategies.

Own the deep reasoning layer at the database layer while staying hands-on with production code and queries.

Work cross-functionally across the entire engineering organization to ensure data infrastructure decisions support company-wide product outcomes.

Evaluate new data technologies and patterns to determine when and how to adopt caching, queues, or streaming for specific workloads.

Requirements

Hands-on experience working with databases inside the product, owning OLTP access patterns, indexing, query optimization, and schema design as part of building user-facing applications.

Comfortable both writing code in the product stack and reasoning carefully at the database layer to balance tradeoffs between consistency, latency, and operational simplicity.

Deep expertise with a major relational engine (Postgres strongly preferred) in high-volume production; experience migrating workloads (e.g., MongoDB → Postgres) is a strong plus.

Expertise in schema design, indexing, query optimization, and zero-downtime migrations on large, live tables that serve high traffic.

Experience scaling systems through significant traffic and data growth, where understanding access patterns at scale is a survival skill, such as in advertising analytics, fintech or trading systems, large-scale consumer SaaS, or marketplaces.

Strong software engineering ability, including writing, reviewing, and shipping production code rather than focusing solely on SQL or ad-hoc analysis.

Flexible problem solving to navigate ambiguous requirements and evolving priorities while maintaining system integrity.

Strong written and verbal communication skills to articulate complex data architecture decisions to both technical and non-technical stakeholders.

Deep sense of personal ownership and accountability for data reliability, performance, and long-term platform health.

Builder mentality focused on creating abstractions and platform primitives that prevent teams from reinventing the same patterns.

Nice to Haves

Experience building shared platform primitives, including data-sync tooling, ORM best practices, caching (Redis), search integrations, or queues and event streaming.

Experience with payments or financial data that demands strict correctness, auditability, and compliance awareness.

Experience with cloud infrastructure and managed services that support scalable, resilient data platforms.

Practical notes

This role is 100% remote and can be based anywhere in the United States or Canada, or anywhere in Mexico or Colombia.

There are no specified hours, travel requirements, visa details, or application deadlines listed in this posting.