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As a Senior Data Engineer at Regard, you will own the design, development, and production deployment of the data services that power the Regard platform. From ingesting and standardizing clinical data across health systems to making it reliably available for downstream product, analytics, and machine learning workflows, you'll build and evolve the infrastructure that enables the platform. This includes analyzing and tuning Spark workloads and partitioning strategies to control costs, adapting to upstream breaking changes, and enforcing rigorous data quality standards so our analytics are as dependable as our application code. We prioritize transparent, code-driven systems over black-box services, and you'll help architect the data platform that supports that philosophy.   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: - Collect, model, and consolidate data into the data platform to support analytics, ML development, and research initiatives - Design, build, and evolve data models and pipelines that reliably transform and deliver data to downstream consumers - Own data quality in collaboration with engineering teams, ensuring datasets are trustworthy and production-ready - Partner closely with product to deliver analytics and actionable insights to internal and external stakeholders - Own the reliability and day-to-day operation of the data platform and its pipelines through proactive monitoring, alerting, and operational management Minimum Qualifications: - Bachelors degree in Computer Science, Mathematics, Statistics, or a related field, or equivalent practical experience - 5+ years of experience in data engineering roles - 3+ years of experience using PySpark to build data pipelines - 3+ years of experience in public cloud provider technologies (AWS tooling such as S3, EMR, or Athena) - Strong proficiency in Python and SQL - Hands-on experience across the full data stack, with particular depth in data modeling and pipeline design - 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, Dagster, Clickhouse, PostgreSQL, FastAPI, Metabase - Experience working with healthcare data, including HIPAA compliance, data de-identification, and familiarity with open data standards such as OMOP CDM - Experience building and supporting data pipelines for ML workflows, including model training, validation, deployment, and ongoing performance evaluation 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 on