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HeartFlow is a publicly traded medical technology company (HTFL) pioneering AI-driven cardiac diagnostics to address coronary artery disease, the #1 cause of death worldwide. The company's flagship product, HeartFlow FFR_CT Analysis, uses cutting-edge AI to provide non-invasive cardiac assessment and has been used for over 500,000 patients globally across the US, UK, Europe, Japan, and Canada.
As Staff Application Database Architect, you will be the backend database expert responsible for the production OLTP systems powering HeartFlow's clinical and operational platform. This is a hands-on, high-impact role where you'll spend the majority of your time designing relational database schemas, writing and tuning high-performance queries, and working directly within Python/Django services to solve real data access challenges. You'll set the architectural direction for how clinical imaging and operational data is structured, accessed, and governed across the AWS-based platform.
Key responsibilities include:
• Design, build, and own OLTP database systems powering clinical and operational applications. Take hands-on ownership of schema design, query optimization, indexing, partitioning, connection pooling, and caching strategies for high-throughput, low-latency web services.
• Drive application data access and ORM strategy by defining best practices for how Python/Django services interact with databases via Django ORM. Solve real-world problems including N+1 queries, lazy-loading pitfalls, transaction isolation, connection pool exhaustion, and read/write splitting.
• Own database performance and DBA excellence by setting direction for database operations—uptime, capacity, backups, recovery, schema evolution, and incident response. Establish SLOs, observability, and runbooks in partnership with engineering and SRE teams.
• Lead transactional data modeling for operational systems, owning conceptual, logical, and physical data models. Drive consistent representation of patients, studies, cases, results, and devices while stewarding master and reference data for high-integrity clinical applications.
• Champion compliance, security, and privacy by ensuring data architectures strictly adhere to FDA, HIPAA, GDPR, and other applicable standards. Partner with Quality, Regulatory, InfoSec, and Privacy teams to embed compliance into the data lifecycle by design.
• Support data lake and analytics handoff (bonus scope) by partnering with IT and Systems Engineering to ensure OLTP source systems produce clean, well-modeled data for downstream analytics pipelines.
• Contribute to enriching the transactional data model with semantics—metadata and controlled vocabularies—so AI agents and downstream consumers can reliably retrieve and reason over clinical and operational information.
Required expertise: Deep hands-on experience with relational databases (PostgreSQL, MySQL, Aurora, or equivalent) supporting production web applications. Expert-level fluency in SQLAlchemy and/or Django ORM. Strong understanding of connection pooling, caching (Redis/Memcached), transaction management, and query optimization. Experience with AWS infrastructure, database replication, and high-availability/disaster-recovery patterns. Familiarity with healthcare data standards (HL7, FHIR) and regulated environments is a plus. Exposure to data lakes, analytics pipelines, or AI-enablement work is advantageous.
