Senior Data Engineer - AI Empowerment

Heartflow•Rohnert Park, CA

18h

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. Their flagship product, the Heartflow FFRCT Analysis, is an AI-driven, non-invasive cardiac test providing a color-coded, 3D model of a patient’s coronary arteries to indicate the impact blockages have on blood flow. Heartflow offers the first AI-driven non-invasive integrated heart care solution across the CCTA pathway, helping clinicians identify stenoses (RoadMap™Analysis), assess coronary blood flow (FFRCT Analysis), and characterize atherosclerosis (Plaque Analysis). The company is publicly traded (HTFL), has received international recognition, is supported by medical societies, cleared for use in multiple countries, and has been used for over 500,000 patients worldwide. As Heartflow continues to revolutionize precision heartcare through AI-driven solutions, they are seeking a proactive, self-starting Senior Data Engineer - AI Empowerment. This role focuses on architecting the infrastructure to empower business processes with AI, specifically leveraging the data lake to fuel advanced models. The Senior Data Engineer will move beyond simple ETL to build robust, observable data products that form the foundation for AI enablement, architecting data pipelines that integrate with Google Vertex AI and Claude to automate complex business workflows. The role acts as a technical lead, balancing high-level AWS infrastructure management with the mission of making data lake assets "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.