Senior Data Engineer - AI Empowerment

Heartflow•Rohnert Park, CA

About The Position

Heartflow is a medical technology company that uses cutting-edge technology to advance the diagnosis and management of coronary artery disease. Their flagship product, the Heartflow FFR CT Analysis, is an AI-driven, non-invasive cardiac test that provides a color-coded, 3D model of a patient’s coronary arteries to indicate the impact of blockages on blood flow. Heartflow offers an AI-driven integrated heart care solution that helps clinicians identify stenoses (RoadMap™Analysis), assess coronary blood flow (FFR CT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). The company is publicly traded (HTFL), has received international recognition, is supported by medical societies, and is cleared for use in multiple countries, having been used for over 500,000 patients worldwide. Heartflow is seeking a proactive, self-starting Senior Data Engineer - AI Empowerment to architect the infrastructure necessary to empower business processes with AI, leveraging the company's data lake to fuel advanced models. This role involves moving beyond simple ETL to building robust, observable data products that serve as the foundation for AI enablement, and architecting data pipelines that integrate with Google Vertex AI and Claude to automate complex business workflows. The Senior Data Engineer will act as a technical lead, managing high-level AWS infrastructure and ensuring data lake assets are "AI-ready" for the entire organization.

Requirements

Expert proficiency in Python (specifically pyiceberg, boto3, polars, and pandas) and SQL.
Hands-on experience integrating data pipelines with Google Vertex AI and utilizing Claude for natural language processing tasks.
Deep hands-on experience with ECS (Fargate/EC2), Redshift, and Athena.
Mastery of Dagster data pipeline concepts, including Software-Defined Assets and declarative orchestration.
Strong experience in Cube Dev semantic modeling and building reporting layers for complex business workflows.
Proven track record in developing data systems that enable AI/ML capabilities or advanced business process automation.
B.S. or M.S. in Computer Science, Data Engineering, or a related field.
5+ years of Data Engineering experience, with significant time spent in AWS environments and a background in enabling AI/ML workflows.
Demonstrated ability as a self-starter with experience mentoring peers and leading technical projects.

Responsibilities

Build and manage complex data pipelines utilizing the Dagster framework to orchestrate data flows into Google Vertex AI for model training and deployment.
Work closely with stakeholders from requirements gathering to training and ongoing support.
Design and maintain specialized pipelines that leverage Claude to automate business processes, ensuring high accuracy and context-aware outputs from our data lake.
Enable departments to leverage AI-powered insights by providing clean, governed, and structured data sets optimized for LLM consumption.
Support a unified semantic model in Cube (Cube.js) to provide consistent metrics that fuel both AI agents and human-centric dashboards.
Manage and optimize high-performance storage and query layers using Iceberg, Amazon Redshift, and Athena to support the data-intensive needs of AI applications.
Lead data governance initiatives to ensure "AI-readiness" and provide technical mentorship to junior engineers on best practices for AI-centric data engineering.
On-call support for 24/7 critical business processes.