Data Engineer

Regard

$120K — $150K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • BS in Computer Science, Mathematics, Statistics, or equivalent experience
  • 3+ years in a data engineering role
  • Proven experience building and maintaining production-level data pipelines
  • Strong proficiency in Python and SQL
  • Experience with distributed data processing frameworks, especially PySpark
  • Familiarity with cloud-based platforms, preferably AWS
  • Experience with LLM-assisted development and awareness of its implications
  • Willing to provide on-call support for data systems.

Responsibilities

  • Build and maintain robust data pipelines for analytics and machine learning
  • Enhance data models and transformations for reliable data delivery
  • Collaborate with engineering to address and rectify data quality issues
  • Monitor and maintain the data platform and its workflows
  • Work alongside Product and Research teams to provide actionable data insights
  • Analyze pipeline failures and data discrepancies for swift resolution
  • Optimize data processing and storage for efficiency and scalability

Benefits

  • Eligible for equity participation
  • 99% employer-paid health benefits including Medical, Dental, and Vision
  • 18 PTO days plus a holiday break each year
  • Monthly wellness budget to promote health
  • Team retreats and social events for team bonding
  • Sabbatical program to encourage long-term growth and rest
Full 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.

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

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