About this role
As a Data Engineer at Regard, you'll build and maintain the data pipelines and infrastructure that turn raw clinical and product data into the metrics, insights, and capabilities that drive our product decisions, analytics, and AI research. We run an engineering-first stack that prioritizes transparent, code-driven systems over black-box services, and you'll contribute to the continued growth and reliability of our data platform.
Working closely with Product, Clinical, Engineering, and Research teams, you'll develop pipelines that bring disparate datasets together into cohesive models, support analytics initiatives, and help ensure the quality and availability of critical datasets. You'll work across the full data stack — from our AWS lakehouse to analytics, APIs, and research datasets — while growing your expertise in distributed data processing, data modeling, and platform operations.
About Regard
Regard's mission is to bring world-class healthcare to everyone. Our technology reasons through a patient's entire medical record to recommend diagnoses that would otherwise be missed, in real time at the point of care, during chart review, and in population-wide screening to identify patients who qualify for lifesaving treatment.
We work alongside some of the top health systems in the country to lead the change this industry needs. We're excited by challenges, mission-oriented work, and meaningful relationships. We want you to join us.
Our Tech Stack:
Lakehouse & processing: Python, SQL, Amazon S3 and S3 Tables, Apache Iceberg, PySpark, EMR Serverless, AWS Glue, Athena
Orchestration & infrastructure: Dagster, Kubernetes, Pulumi, GitLab CI/CD
Data services & analytics: PostgreSQL, ClickHouse, FastAPI, Metabase
Responsibilities:
Build and evolve pipelines that make clinical, application, and reference data available for product development, analytics, and research
Develop and improve data models that bring disparate datasets together into reusable, cohesive views — revealing connections across clinical workflows and product activity
Partner with Product and Clinical teams to explore datasets, develop meaningful measures of adoption and impact, and deliver insights through visualization
Optimize data processing workloads and storage patterns, using experiments and benchmarks to improve performance, scalability, and cost efficiency
Build APIs, tools, and automation that make data easier to discover and use across the organization
Contribute data workflows and datasets that support clinical AI development and evaluation in partnership with Research and Engineering
Take projects from idea through code review, testing, deployment, and production ownership — making the resulting datasets trustworthy, well-documented, and accessible under appropriate privacy controls
Minimum Qualifications:
BS in Computer Science, Mathematics, Statistics, a related field, or equivalent practical experience
3+ years of experience in a data engineering role
Experience building production data pipelines and bringing multiple data sources together into useful data models
Proficiency in Python and SQL, with experience using version control, automated tests, and code review to deliver maintainable software
Experience with distributed data processing frameworks such as PySpark and cloud-based data platforms (AWS preferred)
Willingness to participate in on-call operational support for owned systems
Preferred Qualifications:
Experience with Apache Iceberg or other lakehouse table formats, Dagster or a comparable orchestrator, and scalable data processing patterns
Familiarity with healthcare data, HIPAA requirements, de-identification, and standards such as FHIR, OMOP CDM, or ICD-10
Experience translating product questions into analytical datasets and visualizations, or building data services with tools such as PostgreSQL, ClickHouse, or FastAPI
Practical experience with LLM-assisted development, including reviewing generated code and independently validating results
Exposure to training and evaluation datasets, clinical NLP or LLM workflows, or tools that give AI assistants controlled access to data
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.
Recruitment Fraud Notice Regard only conducts hiring through official @regard.com email addresses. We will never ask candidates to pay fees, purchase equipment, or share sensitive personal information (such as Social Security numbers or bank details) during the interview process. If you receive an email about a job opportunity at Regard from a non-regard.com email address, it is not from us.