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HeartFlow is a publicly traded medical technology company (HTFL) pioneering AI-driven cardiac diagnostics. The company's flagship product, HeartFlow FFR_CT Analysis, is a non-invasive AI test that provides 3D models of coronary arteries to help clinicians assess blood flow and identify blockages. Used by over 500,000 patients worldwide and cleared in the US, UK, Europe, Japan, and Canada, HeartFlow is advancing precision heart care.
As Staff Application Database Architect, you will be the backend database expert for HeartFlow's production applications and web services powering clinical and operational platforms. This is a hands-on technical role where you'll spend the majority of your time designing OLTP schemas, writing and tuning high-performance queries, and working directly within Python/Django services to solve real data access problems. You'll set 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 transactional databases, design schemas, write and optimize complex queries, and implement performance improvements including indexing, partitioning, connection pooling, and caching 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 like N+1 queries, lazy-loading pitfalls, transaction isolation, connection pool exhaustion, and read/write splitting. Review and contribute to high-impact schema and query changes.
• Own database performance and DBA excellence by setting direction for database operations including uptime, capacity, backups, recovery, schema evolution, and incident response. Establish SLOs, observability, and runbooks; partner with engineering and SRE teams to keep mission-critical clinical workloads fast, reliable, and secure.
• Lead transactional data modeling by owning conceptual, logical, and physical data models for operational systems. Drive consistent representation of patients, studies, cases, results, and devices, and steward master and reference data for high-integrity clinical applications.
• Champion compliance, security, and privacy by ensuring data architectures, flows, and access controls 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, Research, and Systems Engineering to ensure OLTP source systems produce clean, well-modeled data feeding downstream Data Lake and analytics pipelines.
• Advance semantic structure for AI agent context (bonus scope) by contributing to enriching HeartFlow's transactional data model with metadata and controlled vocabularies so AI agents and downstream consumers can reliably retrieve and reason over clinical and operational information.
Required experience includes deep, hands-on expertise in relational databases (PostgreSQL, MySQL, Aurora, or equivalent) supporting production web applications, with strong experience in schema design, query optimization, indexing, partitioning, replication, and HA/DR. You need strong experience building backend data layers for web applications and services in Python, with expert-level fluency in SQLAlchemy and/or Django ORM, and deep understanding of connection pooling, caching (Redis/Memcached), and transaction management. Experience with AWS data services, Data Lake, analytics pipelines, or AI-enablement work is a plus.
