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Salary: USD 190,000 - 250,000 / annual
HeartFlow is a publicly traded medical technology company (HTFL) pioneering AI-driven solutions for coronary artery disease diagnosis and management. 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 750,000 patients worldwide 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 technical role where you will 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 problems. You will also 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 (PostgreSQL, MySQL, Aurora) 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. 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 maintain mission-critical clinical workloads.
- Lead transactional data modeling for operational systems, owning conceptual, logical, and physical data models. Drive consistent representation of patients, studies, cases, results, and devices; steward master and reference data for high-integrity clinical applications.
- Advance semantic structure for AI agent context by enriching the transactional data model with metadata and controlled vocabularies so AI agents and downstream consumers can reliably retrieve and reason over clinical and operational information.
- 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 the 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.
You are passionate about building rock-solid transactional databases that clinicians and applications depend on daily, championing engineering excellence and rigorous practices, staying hands-on with code and query plans, and fostering constructive collaboration across teams.
REQUIREMENTS:
- Bachelor's degree in Computer Science, Engineering, or related discipline, or equivalent experience. Master's degree preferred.
- 10+ years of relevant industry experience as a backend/application database engineer or data architect, with deep, hands-on OLTP experience supporting production web applications or web services.
- Deep, hands-on expertise in relational databases (PostgreSQL, MySQL, Aurora, or equivalent) supporting production web applications — schema design, query optimization, indexing, partitioning, replication, and HA/DR.
- Strong experience building backend data layers for web applications and services in Python, with expert-level fluency in SQLAlchemy and/or Django ORM. Deep understanding of connection pooling, caching (Redis/Memcached), transaction management, and common ORM pitfalls at scale.
- Expert-level conceptual, logical, and physical data modeling for transactional/OLTP workloads (3NF or equivalent), including modeling for healthcare/clinical domains.
- Performance tuning, partitioning, indexing strategy, replication, HA/DR, and operational excellence for production relational databases.
- Building data systems in modern cloud ecosystems — AWS preferred (RDS/Aurora, ElastiCache, etc.) — with strong grasp of cost, security, and reliability tradeoffs at scale.
- Working with clinical, imaging, or device data under regulatory regimes such as FDA, HIPAA, and GDPR; familiarity with healthcare data standards (FHIR, HL7, DICOM) is a strong plus.
- Technical leadership experience mentoring senior engineers, driving cross-team architectural decisions, establishing engineering standards, and influencing technology selection across multiple teams and programs.
Nice to have (bonus, not required):
- Familiarity with Data Lake or lakehouse concepts (S3, Glue, Spark, Airflow).
- Exposure to metadata, schema registries, ontologies, or semantic layers that make data usable by AI/agentic systems.
- Data warehousing/ETL experience.
