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Regard

Data Engineer

Posted 15 Days Ago
Hybrid
San Francisco, CA, USA
160K-190K Annually
Mid level
Hybrid
San Francisco, CA, USA
160K-190K Annually
Mid level
Build and maintain production data pipelines and models to support analytics, ML, and research. Ensure data quality and availability, operate and monitor the data platform, investigate failures, optimize performance and costs, and collaborate with Product, Engineering, and Research teams.
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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 engineering teams to identify and resolve data quality issues, helping ensure datasets are accurate and trustworthy

  • Support the operation, monitoring, and maintenance of the data platform and its pipelines

  • Collaborate with Product, Engineering, and Research teams to deliver data and insights that inform business and product decisions

  • Investigate pipeline failures, data inconsistencies, and upstream changes, contributing to timely resolution and continuous improvement

  • Help optimize data processing workloads and storage patterns to improve performance, scalability, and cost efficiency

Minimum Qualifications:

  • BS in Computer Science, Mathematics, Statistics, a related field, or equivalent practical experience

  • 3+ years of experience in data engineering role

  • Experience building and maintaining data pipelines and data models in a production environment

  • Proficiency in Python and SQL

  • Experience working with distributed data processing frameworks such as PySpark

  • Experience with cloud-based data platforms and services (AWS preferred)

  • Practical experience with LLM-assisted development, with an understanding of its capabilities and limitations

  • Willingness to participate in on-call operational support for owned systems

Preferred Qualifications:

  • Experience with one or more of the following technologies: Apache Iceberg, AWS Athena, Dagster, Clickhouse, PostgreSQL, FastAPI, or Metabase

  • Experience supporting data quality, monitoring, and observability initiatives

  • Familiarity with healthcare data, including HIPAA compliance, de-identification, or healthcare data standards such as OMOP CDM

  • Experience building or supporting data pipelines used for machine learning training, evaluation, or production workflows

  • Experience working with cross-functional teams in a fast-paced startup environment

Hybrid Work | Location | Work Authorization

  • For this role, Regard is currently only considering candidates who are authorized to work in the US without visa sponsorship, and are within the New York City, Los Angeles, or San Francisco metro areas

  • We expect our Engineers to be in the office on Tuesdays and Thursdays. We also require more frequent in-office work during the onboarding period and team onsite weeks up to once per month

  • We will provide relocation assistance to anyone who does not already reside in the NYC metro area

  • We prefer hiring people within commuting distance of our offices because we value getting together in person regularly

  • For those who enjoy working from our LA or Manhattan offices on a more regular basis, we offer catered lunches and other fun perks

  • Additionally, hybrid employees have the flexibility to work from locations outside of their home office from up to 6 weeks per year

Comp | Perks | Benefits

  • Eligible for equity

  • 99% employer paid health benefits (Medical, Dental, and Vision) + One Medical subscription

  • 18 PTO days/yr + 1 week holiday break

  • Monthly health & wellness budget

  • Company-sponsored team retreat + social events

  • A sabbatical program

Our goal at Regard is to provide and maintain a work environment that fosters mutual respect, professionalism and cooperation. Regard is proud to be an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, alienage or citizenship status, age, disability or handicap, sex, gender identity, marital status, familial status, veteran status, sexual orientation or any other characteristic protected by applicable federal, state or local laws. We celebrate diversity and are proud of our supportive, inclusive workplace.

 

All candidates must successfully complete a background check as part of the hiring process.

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