Senior Data Engineer
About The Position
As a Senior Data Engineer at Regard, you will own 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 be responsible for architecting and evolving these systems. You will set the technical standards and take full ownership of our data platform's reliability, performance, and data quality, going beyond basic monitoring to tackle real operational challenges. This includes analyzing and tuning Spark workloads and partitioning strategies to control costs, handling breaking upstream changes, and enforcing rigorous data quality standards so our analytics are as dependable as our application code. 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: Apache Iceberg, EMR, PySpark, Dagster, Clickhouse, PostgreSQL, Metabase Backend: Python (FastAPI, Flask), Redis, Celery Infrastructure & DevOps: Docker, Kubernetes, AWS (SQS, SNS), GitLab CI/CD APIs & AI: OpenAPI, OpenAI (GPT models)
Requirements
- Bachelors degree in Computer Science, Mathematics, Statistics, or a related field, or equivalent practical experience
- 5+ years of experience in data engineering roles building and operating production data pipelines
- 3+ years of experience working with public cloud platforms (e.g., AWS services such as Glue, Kinesis, or EMR)
- Strong proficiency in Python and SQL
- Hands-on experience across the full data stack, with particular depth in data modeling and pipeline design
- Willingness to participate in on-call operational support for owned systems
- Ability to travel up to four weeks per year for company co-working and/or retreat weeks
- Strong verbal and written communication skills
Nice To Haves
- 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
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
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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
