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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 500,000 patients worldwide across the US, UK, Europe, Japan, and Canada.
The Director of IT, Data Services and AI Enablement leads a small team responsible for enterprise data infrastructure, systems integrations, automation, and AI enablement. This strategic leadership role drives the development and optimization of HeartFlow's enterprise data platform, delivering scalable, governed, high-quality data solutions that accelerate insights and enable AI/ML capabilities.
Key responsibilities include:
Data Infrastructure & Engineering: Design, develop, and manage the enterprise data infrastructure platform owning the complete data lifecycle—ingestion (batch, streaming, APIs), transformation (ETL/ELT), modeling, storage, integration, and delivery. Oversee data pipelines, modeling, and reporting solutions while embedding governance, data quality, monitoring, and observability. Ensure data accuracy and accessibility across systems. Design and operationalize an enterprise semantic layer (e.g., Cube Cloud) for secure, standardized data access.
Analytics, AI Enablement & Strategy: Drive the company's AI-readiness by ensuring data architectures are clean, structured, and available for ML and generative AI workloads. Enable self-service analytics and data discoverability through tools like Tableau, semantic layers, and data catalogs. Lead evaluation and implementation of AI-enabled tools. Partner with business units to identify and prioritize high-value AI use cases. Align data investments with corporate and digital transformation strategies.
Integration & Automation: Direct design and implementation of integrations across enterprise applications. Ensure reliability, scalability, and alignment with enterprise architecture. Lead development of automated workflows that reduce manual processes and improve operational efficiency.
Governance & Continuous Improvement: Support governance for data management, system integrations, and responsible AI use. Establish KPIs for data quality, adoption, and automation impact. Identify and implement improvements to enhance reliability and user experience. Partner with vendors to evaluate technologies aligned to enterprise strategy. Drive FinOps initiatives to optimize cloud infrastructure spend.
