Staff Software Engineer, PostgreSQL

Beacon Biosignals•Boston, MA

1d•Remote

About The Position

Beacon Biosignals is hiring two engineers for its Datastore team, which provides the foundational data model, centralized repository, and API for brain data collected from clinical studies. The Datastore supports analytical tools, services, and applications used by scientists, clinicians, and partners. This role focuses on backend data infrastructure, including PostgreSQL data models, Kafka-driven event pipelines, and the GraphQL API, rather than frontend development or end-user product surfaces. Engineers will lead the design of complex Datastore systems, own dataset snapshot pipelines into the warehouse, and collaborate across platform, application, scientific, clinical, and product teams to develop APIs and services for clinical studies and digital health products. Beacon is hiring for two profiles with the same core requirements: a Datastore Systems role focused on platform breadth, including event pipelines, GraphQL, core data models, and integrations; and a PostgreSQL & Data Modeling role focused on database design, performance, operations, and access controls. Applicants are asked to indicate which profile interests them most. The GraphQL API is generated from the PostgreSQL schema using PostGraphile, so schema decisions also affect the API. Row-level security is applied to effectively every table to protect clinical data across studies and partners. The role is 100% remote from anywhere in the U.S., with in-person office hubs in Boston, New York City, and Paris. Success involves leading architecture and technical design, translating stakeholder requirements into platform solutions, debugging cross-system issues, maintaining high standards for data integrity and maintainability, mentoring engineers, planning work, and improving operational robustness and usability through documentation, tools, and dashboards.

Requirements

At least 7 years of backend development experience, including at least 3 years focused on data platforms and backend infrastructure for data-centric applications.
High proficiency in at least one relevant technical area: data modeling, distributed systems, API design, or database engineering.
Strong SQL proficiency and production experience using PostgreSQL as an application database; ability to write and tune queries and reason about schema design, indexes, and query plans.
Hands-on data streaming and event-processing experience with Kafka or an equivalent such as RabbitMQ, Pulsar, Amazon Kinesis, or another cloud-based equivalent.
Proficiency in Julia or Python.
Experience deploying and operating services in containerized environments, with familiarity with Kubernetes and Infrastructure as Code tools such as Terraform and/or Helm.
Track record of mentoring engineers and improving team practices, tooling, test coverage, or documentation.
Collaborative mindset and ability to work across disciplines.
Excellent written and verbal communication skills, particularly in asynchronous and remote-friendly environments.
Self-directed approach and a track record of thriving in hybrid or fully remote teams.
Experience with, or interest in, using LLM-assisted or agentic coding tools in production, with sound judgment about appropriate guardrails.
Applicants should indicate whether they are most drawn to the Datastore Systems role or the PostgreSQL & Data Modeling role.

Nice To Haves

Experience with Julia; it is a core Datastore language, though candidates may learn it on the job.
For the Datastore Systems profile: GraphQL and TypeScript/JavaScript (Node.js) experience, and ability to lead end-to-end event-driven pipeline design.
For the PostgreSQL & Data Modeling profile: deep PostgreSQL expertise, including query planning, index selection, EXPLAIN (ANALYZE), schema design and constraints, temporal data modeling, zero-downtime migrations, backfills and verification, and production operations such as upgrades, replication, backup and restore, connection pooling, bloat, vacuum behavior, and extensions.

Responsibilities

Lead design and architecture for complex Datastore projects and systems, weighing implementation trade-offs and supporting decisions with data.
Partner with product managers, scientific and clinical stakeholders, and development and support teams to translate requirements into integrations, services, and platform solutions.
Contribute to broader product and technical decisions, not only implementation.
Debug and profile ambiguous problems that cross system boundaries, including in codebases outside the Datastore team’s purview.
Implement features with attention to data integrity, design soundness, product awareness, and maintainability.
Draft RFCs, lead complex feature discovery and technical design, solicit input, and help the team align on decisions.
Plan individual work and contribute to team planning, balancing speed, generalizability, technical debt, and stakeholder needs.
Teach and mentor engineers, provide actionable feedback, and potentially act as a project tech lead or engineering-practice coordination point.
Use stakeholder and partner feedback to improve Datastore operational robustness and ease of use through documentation, tools, and dashboards.
Own pipelines that deliver dataset snapshots into the warehouse.
For the Datastore Systems profile, design across the platform, including GraphQL APIs, event-driven pipelines, and dependent services; address producers, consumers, replay, idempotency, and consumer lag.
For the PostgreSQL & Data Modeling profile, lead database modeling, query and performance tuning, schema evolution, production operations, and team education around database design and access controls.