Staff Software Engineer, Data Platform

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $170k - $190k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Beacon Biosignals

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Beacon Biosignals is a company focused on powering precision medicine for the brain. Their EEG neurobiomarker platform is engineered to accelerate clinical trials and enable new treatments for patients with neurological and psychiatric diseases. The platform captures a rich array of the brain's activity in real time and utilizes machine learning to analyze EEG data for treatment efficacy, dose selection, and population stratification. Beacon Biosignals partners with biopharma companies, academic medical centers, and neurotechnology developers to improve the diagnosis and treatment of neurological and psychiatric diseases.

📋 Description

• Lead design and architecture for complex projects and systems within the Datastore • Weigh implementation trade-offs and support decisions with data • Partner with product managers, scientific and clinical stakeholders, development teams, and support teams • Translate requirements into integrations, services, and solutions for scaling Beacon's data platform • Contribute to broader product and technical decisions • Debug and profile ambiguous problems across system boundaries • Improve code structure, test coverage, and tooling • Implement features with high standards for data integrity, design soundness, and maintainability • Draft RFCs and lead feature discovery and technical design phases • Plan individual and team work while balancing speed, generalizability, and technical debt • Teach and mentor engineers; provide actionable feedback • Potentially act as a technical lead or engineering-practice coordinator • Improve operational robustness and ease of use through documentation, tools, and dashboards • Own event pipelines, GraphQL APIs, core data models, third-party integrations, and/or PostgreSQL data modeling, performance tuning, and operations

🎯 Requirements

• 7+ years of backend development experience • At least 3 years focused on data platforms and backend infrastructure for data-centric applications • Highly proficient in at least one of: data modeling, distributed systems, API design, or database engineering • Strong proficiency in SQL and production experience with PostgreSQL as an application database • Experience writing and tuning queries and reasoning about schema design, indexes, and query plans • Hands-on experience with data streaming and event processing using Kafka or an equivalent such as RabbitMQ, Pulsar, Amazon Kinesis, or another cloud-based equivalent • Proficiency in Julia or Python; Julia experience is a strong plus but not required • Experience deploying and operating services in containerized environments • 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 • Excellent written and verbal communication skills • Self-directed approach and experience thriving in hybrid or fully remote teams • Experience with or interest in LLM-assisted or agentic coding tools in a production setting • For the Datastore Systems role: GraphQL and TypeScript/JavaScript (Node.js); end-to-end event-driven pipeline design; leading complex system design across APIs, pipelines, and dependent services • For the PostgreSQL & Data Modeling role: deep PostgreSQL knowledge; query planner, index selection, and EXPLAIN (ANALYZE); data modeling; schema evolution under load; zero-downtime migrations; dual-write transitions; lock avoidance; backfill and verification; PostgreSQL production operations including upgrades, replication, backup and restore, connection pooling, bloat, vacuum behavior, and extensions • Strong fundamentals, care for data infrastructure for health, and willingness to learn

🏖️ Benefits

• Equity • PTO • Other benefits • 100% remote work from anywhere in the U.S. • Asynchronous work practices • In-person office hubs in Boston, New York City, and Paris