Staff Data Architect

This position will play a pivotal technical leadership role in realizing Heartflow’s vision of a single, comprehensive platform to manage heart disease. As a Staff Data Architect, you will lead the data strategy for our medical device system—defining how clinical, imaging, and operational data is structured, stored, accessed, and governed across our AWS-based platform and partner ecosystems.

You will own the architectural roadmap for our transactional databases, analytical Data Lake, and the pipelines that connect them. Operating at the staff level, you will set the standards for data modeling, query performance, and access patterns, partner deeply with Software Engineering, IT, Research, and Systems Engineering, and elevate the semantic structure of our data so that our products—including emerging AI agents—operate on a trustworthy, well-described, and compliance-ready foundation.

• →Lead Data Strategy for the Medical Device System: Define the multi-year data architecture vision spanning transactional databases, Data Lake, and downstream consumers. Translate product, clinical, and regulatory requirements into a coherent data strategy that scales as Heartflow’s portfolio grows.
• →Oversee Database Performance & DBA Excellence: Set direction for database operations across the platform—uptime, capacity, backups, recovery, schema evolution, and incident response. Establish SLOs, observability, and runbooks; partner with engineering and SRE teams to ensure mission-critical clinical workloads remain fast, reliable, and secure.
• →Lead Enterprise Data Modeling: Own conceptual, logical, and physical data models across operational and analytical systems. Drive consistent representation of patients, studies, cases, results, and devices, and steward the master data and reference data needed for high-integrity clinical reporting.
• →Partner with Software Engineering on Query Performance & Access Patterns: Embed with product engineering teams to improve indexing, partitioning, caching, and read/write patterns. Coach engineers on data access best practices, review high-impact query and schema changes, and reduce cost and latency at scale.
• →Architect the Data Lake & Data Pipelines: Partner with IT, Research, and Systems Engineering teams to design and evolve the Data Lake, lakehouse layers, and ingestion/transformation pipelines. Define standards for data contracts, lineage, quality, and governance from source-of-truth systems through curated analytical and ML-ready datasets.
• →Advance the Semantic Structure for AI Agent Context: Lead efforts to enrich Heartflow data with semantics—ontologies, controlled vocabularies, schema registries, and metadata—so that AI agents and downstream consumers can reliably retrieve, reason over, and act on 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.
• →Provide Technical Leadership: As a staff-level technical multiplier, mentor data and software engineers, set engineering standards for data work, influence technology and tool selection, and represent the data architecture function in cross-functional planning, hiring panels, and roadmap reviews.

• Data Architecture & Strategy: Defining multi-year data architecture for complex, regulated platforms—spanning OLTP databases, Data Lakes / lakehouses, streaming pipelines, and downstream analytical and ML consumers.
• Database Engineering & DBA Leadership: Deep expertise in relational and modern cloud databases (e.g., PostgreSQL, Aurora, Snowflake, Redshift, or equivalent) including performance tuning, partitioning, indexing strategy, replication, HA/DR, and operational excellence.
• Data Modeling: Expert-level conceptual, logical, and physical modeling for both transactional and analytical workloads (3NF, dimensional modeling, Data Vault or equivalent), including modeling for healthcare/clinical domains.
• Data Lake & Pipelines: Designing scalable Data Lake / lakehouse architectures (e.g., S3, Iceberg/Delta/Hudi, Glue, EMR, Spark, dbt, Airflow, Kafka) with strong patterns for data quality, lineage, and governance.
• Cloud Platforms: Building data systems in modern cloud ecosystems—AWS preferred—with a strong grasp of cost, security, and reliability tradeoffs at scale.
• Semantic Data & AI Enablement: Working with metadata, schema registries, ontologies, and semantic layers to make data discoverable and usable by humans, applications, and AI/agentic systems.
• Healthcare Data & Compliance: 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.
• Technical Leadership: Mentoring senior engineers, driving cross-team architectural decisions, establishing engineering standards, and influencing technology selection across multiple teams and programs.

• Platform Vision: Realizing the vision of a single, unified data platform that powers Heartflow’s products and AI capabilities.
• Engineering Excellence: Championing high-quality data systems, rigorous review and testing practices, and elevating the technical baseline of the entire team.
• Strategic Ownership: Taking end-to-end ownership of complex architectural domains and operating independently with a high degree of latitude.
• Constructive Collaboration: Fostering open communication across Engineering, IT, Research, and Systems Engineering, and guiding healthy technical debates that result in better outcomes.
• Innovation: Pragmatically evaluating and introducing state-of-the-art data, semantic, and AI-enabling technologies to solve real clinical and operational problems.

• Domain Expertise: Advancing the frontier of Software as a Medical Device (SaMD) and clinical data platforms in the cardiology space.
• Regulatory Innovation: Navigating and innovating within strict regulatory environments (FDA, HIPAA, GDPR) to securely deliver life-saving medical applications.
• AI Agent Data Foundations: Designing the semantic, governance, and retrieval layers that allow AI agents to operate safely, accurately, and with appropriate context over Heartflow data.

• Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent experience. Master’s preferred.
• 10+ years of relevant industry experience in data architecture, data engineering, and/or database engineering, including time spent leading architecture across multiple teams or programs.

A reasonable estimate of the base salary compensation range is $190,000 to $250,000, plus bonus and equity. #LI-Hybrid