Staff Software Engineer

Join Beacon Biosignals as a Staff Software Engineer on the Datastore team. This role focuses on the design and scaling of backend systems for data infrastructure, including PostgreSQL data models, Kafka-driven event pipelines, and the GraphQL API. You will lead the design of complex systems, collaborate with various teams, and mentor other engineers. The ideal candidate has 7+ years of backend development experience, strong proficiency in SQL, and experience with data streaming and event processing.

• Lead the design and architecture for complex projects and systems within the Datastore, making implementation trade-offs based on engineering principles.
• Collaborate with product managers, scientific and clinical stakeholders, and other development teams to translate requirements into new integrations, services, and solutions.
• Mentor other engineers, provide feedback, and act as a tech lead on projects, improving team practices, tooling, test coverage, or documentation.

• You should have experience writing complex SQL queries by hand, and should be prepared to reason about schema design, indexes, and query behavior as a matter of course
• The other will focus on depth in PostgreSQL (data modeling, performance tuning, operations) and supporting all engineers in developing schemas and the access controls that protect clinical data. The core requirements are the same. Tell us which one you are most drawn to in your application
• 7+ years of backend development experience, including at least 3 years focused on data platforms and backend infrastructure for data-centric applications: transactional systems, event pipelines, and the APIs that serve them
• Excellent written and verbal communication skills, especially in asynchronous and remote-friendly environments
• A collaborative mindset: you enjoy working across disciplines and believe people achieve more together than alone
• Highly proficient in at least one technical area relevant to this work: data modeling, distributed systems, API design, or database engineering, with the depth that others on a team come to you for
• Proficiency in Julia or Python; Julia is a core Datastore language, and experience with Julia is a strong plus, but not required — we welcome candidates eager to learn it!
• A self-directed approach, with a track record of thriving in hybrid or fully remote teams
• Strong proficiency in SQL, with production experience working with PostgreSQL as an application database; you write and tune queries fluently and are comfortable reasoning about schema design, indexes, and query plans
• Experience with, or interest in, using LLM-assisted or agentic coding tools in a production setting, with good judgment about what guardrails are needed
• Hands-on experience with data streaming and event processing, using Kafka (our event bus) or an equivalent such as RabbitMQ, Pulsar, or a cloud-based equivalent like Amazon Kinesis
• A track record of mentoring engineers and improving how a team works - practices, tooling, test coverage, or documentation that outlasted your involvement
• Experience deploying and operating services in containerized environments, with familiarity in Kubernetes and Infrastructure as Code (IaC) tools such as Terraform and/or Helm
• Leading the design of complex systems rather than individual components, across the API, the pipelines, and the services that depend on them
• You can lead design across the breadth of the platform
• GraphQL and TypeScript/JavaScript (Node.js) - GraphQL is the Datastore's primary interface, and this profile owns significant parts of it
• Designing event-driven pipelines end to end: producers, consumers, replay, idempotency, and what happens when a consumer falls behind
• Data modeling: you design the schema itself: entities, relationships, and the constraints that make invalid states impossible. Including how to model time, since clinical results get re-scored and corrected and we need to answer "what did this look like when the report was signed?"
• Deep PostgreSQL: you reason fluently about the query planner, index selection, and EXPLAIN (ANALYZE), and why a query that should be fast isn't
• You can be the person the rest of the team comes to about the database
• Making others good at it: you teach, review, and document, because a schema only stays coherent if the team understands it
• We don't expect every candidate to check every box. If you bring strong fundamentals, care about data infrastructure for health, and are excited to learn, we’d love to hear from you!
• Operating PostgreSQL in production, not only designing for it: upgrades, replication, backup and restore, connection pooling, bloat and vacuum behaviour, extensions
• Schema evolution under load: zero-downtime migrations, dual-write transitions, lock avoidance, backfill and verification. Our schema has hundreds of migrations behind it and will have hundreds more