Senior Data Engineer

Heartflow • Rohnert Park, CA

17d • $110,000 - $150,000

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.
We are seeking a proactive, self-starting Senior Data Engineer to architect and scale our data infrastructure, with a specific focus on HRIS, Market Research and Revenue Cycle pipelines, reporting and governance. In this role, you will move beyond simple ETL to building robust, observable data products using Dagster and Cube while ensuring data governance practices and catalog management are consistently maintained. You will act as a technical lead, balancing high-level AWS infrastructure management (ECS, Redshift, Athena) with the mentorship of junior team members to foster a culture of engineering excellence

Requirements

• Languages & Libraries: Expert proficiency in Python (specifically pyiceberg, boto3, polars, and pandas), SQL, DBT, and YAML.
• AWS Ecosystem: Deep hands-on experience with ECS (Fargate/EC2), Redshift (clustering and optimization), and Athena (serverless querying).
• Pipeline Concepts: Mastery of Dagster data pipeline concepts, including Software-Defined Assets and declarative orchestration.
• Modeling: Strong experience in Cube Dev semantic modeling and building reporting layers for complex financial workflows.
• Domain Knowledge: Proven track record in developing Revenue Cycle pipelines and financial reporting systems.
• Reporting Solution: Experience building and supporting Tableau datasets and reports.
• Education: B.S. or M.S. in Computer Science, Data Engineering, or a related field.
• Experience: 5+ years of Data Engineering experience, with significant time spent in AWS environments and a strong background in RCM/Financial data.
• Leadership: Demonstrated ability as a self-starter with experience mentoring peers and leading technical projects.

Responsibilities

• Orchestration & Automation: Build and manage complex data pipelines utilizing the Dagster framework, leveraging AWS ECS for containerized task execution.
• Revenue Cycle Expertise: Design and maintain specialized pipelines and reports for Revenue Cycle Management, ensuring high accuracy for financial data processing.
• Semantic Layer & BI: Support the development of a unified semantic model in Cube (Cube.js) to provide consistent metrics across the organization.
• Modern Data Stack Management: Manage and optimize high-performance data storage and query layers using Iceberg, Amazon Redshift and Athena.
• Mentorship & Governance: Lead data governance initiatives and provide technical mentorship to junior engineers, ensuring adherence to Python and SQL best practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level