REGARD

Data Engineer

REGARD
US San Francisco, CA, US
Onsite 2026-06-21
Announced salary
$140k–$175k
Market rate in San Francisco : $123K - $211K (median $161K) · BLS OEWS 2025

Job description

As a Data Engineer at Regard, you will help build and maintain the data pipelines and infrastructure that turn raw data into the metrics and insights that drive our product decisions and research. We run an engineering\-first stack that prioritizes transparent, code\-driven systems over black\-box services, and you will contribute to the continued growth and reliability of our data platform. Working closely with Engineering and Product teams, you'll develop and improve data pipelines, support analytics and machine learning initiatives, and help ensure the quality and availability of critical datasets. You'll have the opportunity to work across the full data stack while growing your expertise in distributed data processing, data modeling, and platform operations. **About Regard** Our mission is to bring world\-class healthcare to everyone. Regard is an AI\-powered Proactive Documentation platform that advances how care is delivered by reviewing all patient data in the EHR to recommend diagnoses and surface clinical evidence. Regard drafts a note even before the physician sees the patient, enabling an approach that gets documentation right at the point of care \- we call it Proactive Documentation. This improves quality of care, reduces physician burden, and improves hospital finances. We are excited by challenges, mission\-oriented work, and meaningful relationships. We work closely with some of the top health systems in the country and are leading the change that healthcare \- one of the largest and most inefficient industries in the world \- needs. We want you to join us. **Our Tech Stack:** * **Data:** S3, Apache Iceberg, EMR, PySpark, Dagster, Kubernetes, Clickhouse, PostgreSQL, FastAPI, Metabase **Responsibilities:** * Build and maintain data pipelines that support analytics, machine learning development, and research initiatives * Develop and improve data models and transformations that reliably deliver data to downstream consumers * Partner with eng

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