Sr. Staff Platform Engineer, Medical Data

About the position We are looking for a Sr. Staff Platform Engineer to serve as the key steward and architect of our medical data domain. In this role, you will own the integrity of our logical data model, ensuring that every service we build and every integration with customer systems preserves the accuracy and fidelity of our patient data. Your primary focus will be on the interaction between our services and our data. You will define the patterns that allow our systems to interact with complex medical data structures in the most elegant, flexible, and performant way possible. You will act as the guardian of our domain model, ensuring that as we scale, we never compromise on data correctness or structural coherence. This is a leadership role for a hands-on technical visionary. You will solve deep, structural problems regarding data consistency and interoperability. As a key voice on the Architecture Review Board (ARB), you will be the ultimate gatekeeper for decisions involving the data model, ensuring that our architecture evolves to support new clinical capabilities without accruing technical debt. If you are an expert in healthcare data standards and modern cloud engineering, this is your chance to build a legacy.

Responsibilities

• Domain Model Stewardship & Service Interaction: You will define and enforce the integrity of our logical data model. You will architect the patterns for how all internal services and external integrations interact with this model, ensuring data accuracy and structural flexibility are preserved across the entire platform.
• High-Throughput Ingestion Architecture: You will architect and optimize our ingestion pipelines to handle massive bursts of DICOM images and HL7 messages without latency or data loss.
• Standards & Interoperability: You will lead the strategy for FHIR, HL7, and DICOM interoperability, ensuring our platform speaks the language of modern healthcare fluently.
• Automate Compliance: You will design systems that enforce HIPAA, ISO 27001, and SOC2 requirements at the infrastructure and code level. You will build "compliance as code" to ensure audit readiness without manual toil.
• Data Governance: You will define the patterns for data residency, retention, and deletion, ensuring we meet strict legal and contractual obligations across global deployments.
• Systemic Data Consistency: You will solve hard problems regarding distributed data consistency, helping us move away from tight coupling while ensuring data correctness across services.
• Elevate the Platform: You will be the subject matter expert (SME) for healthcare data within the engineering organization, mentoring Staff and Senior engineers on the nuances of medical data standards and distributed data patterns.

Requirements

• Deep Healthcare Data Expertise: 10+ years of engineering experience with a specific focus on healthcare data. You are an expert in DICOM (tags, transfer syntaxes, WADO/QIDO) and HL7/FHIR.
• Scale & Performance: Proven track record of building data pipelines that handle terabytes of medical imaging data. You understand the specific storage and retrieval challenges of pixel data vs. metadata.
• Language Fluency & Strategy: Deep expertise in TypeScript/Node.js is required. As we pivot performance-critical paths toward Go, experience leading similar language transitions or strong Go proficiency is highly desirable.
• Deep expertise in schema design for both SQL (PostgreSQL) and NoSQL environments.
• Experience with data lakes and warehousing (BigQuery/Snowflake) in a healthcare context.
• Experience with stream processing (Kafka/Dataflow) for real-time DICOM and HL7 feeds.
• Expertise in container orchestration (Kubernetes) at scale.
• Compliance expertise: You have built systems that are HIPAA/GDPR compliant from the ground up and understand the technical implications of PHI (Protected Health Information) protection.
• Communication at Scale: You can effectively communicate the business value of architectural investments to executive leadership while diving deep into the code with engineers.

Nice-to-haves

• Imaging Physics Knowledge: Understanding of the physics of medical imaging (CT, MRI, X-Ray) and how it impacts data storage and rendering.
• AI/ML Pipeline Experience: Experience architecting data flows that feed AI models for clinical decision support.
• PACS/VNA Architecture: Experience architecting or operating Picture Archiving and Communication Systems (PACS) or Vendor Neutral Archives (VNA).

Benefits

• Medical
• Dental
• Vision
• “Use as needed” vacation policy
• participation in our employee option program

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