Staff Application Database Architect

Heartflow•San Francisco, CA

8d•$190,000 - $250,000•Hybrid

About The Position

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the Heartflow FFRCT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. Heartflow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFRCT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare. Heartflow is a publicly traded company (HTFL) that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 500,000 patients worldwide. As a Staff Application Database Architect, you will be the backend database expert behind the production applications and web services that power Heartflow's clinical and operational platform. This is a hands-on role: the majority of your time will be spent designing OLTP schemas, writing and tuning high-performance queries, and working directly inside our Python/Django services to solve real data access problems — alongside setting the architectural direction for how clinical, imaging, and operational data is structured, accessed, and governed across our AWS-based platform. Exposure to Data Lake, analytics pipelines, or AI-enablement work is a plus.

Requirements

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 the Django ORM. Deep understanding of connection pooling, caching (Redis/Memcached), transaction management, and common ORM pitfalls at scale.
Expert-level conceptual, logical, and physical 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 a 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 (e.g., FHIR, HL7, DICOM) is a strong plus.
Mentoring senior engineers, driving cross-team architectural decisions, establishing engineering standards, and influencing technology selection across multiple teams and programs.
Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent experience.
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.

Nice To Haves

Familiarity with Data Lake or lakehouse concepts (e.g., S3, Glue, Spark, Airflow) for the minor analytics-handoff portion of the role.
Exposure to metadata, schema registries, ontologies, or semantic layers that make data usable by AI/agentic systems.
Master's degree preferred.
Data warehousing/ETL experience is a plus.

Responsibilities

Design, Build & Own OLTP Database Systems: Take hands-on ownership of the transactional (OLTP) databases powering Heartflow's clinical and operational applications. Design schemas, write and optimize complex queries, and directly implement performance improvements — indexing, partitioning, connection pooling, caching — for high-throughput, low-latency web services.
Drive Application Data Access & ORM Strategy: Define and implement best practices for how our Python/Django services interact with the database via the Django ORM. Solve real-world problems like N+1 queries, lazy-loading pitfalls, transaction isolation, connection pool exhaustion, and read/write splitting; review and directly contribute to high-impact schema and query changes in application code.
Own Database Performance & DBA Excellence: Set direction for database operations — 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: Own conceptual, logical, and physical data models for our operational systems. Drive consistent representation of patients, studies, cases, results, and devices, and steward the master and reference data needed for high-integrity clinical applications.
Advance the Semantic Structure for AI Agent Context: Contribute to enriching Heartflow's 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.
Champion Compliance, Security & Privacy: Ensure 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 & Analytics Handoff (minor, bonus scope): For candidates with the background, partner with IT, Research, and Systems Engineering to ensure OLTP source systems produce clean, well-modeled data that feeds downstream Data Lake and analytics pipelines. This is a supporting responsibility for the right candidate, not a requirement of the role.
Advance the Semantic Structure for AI Agent Context (minor, bonus scope): For candidates with the background, contribute to enriching Heartflow's 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.