Senior Data Engineer

Regard

$120K — $150K *
Healthcare
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field, or equivalent experience
  • 5+ years of data engineering experience
  • 3+ years of experience with PySpark for data pipeline construction
  • 3+ years working with public cloud technologies (AWS tools like S3, EMR, or Athena)
  • Strong Python and SQL skills
  • Experience with end-to-end data stack, focusing on data modeling and pipelines
  • Knowledge of LLM-assisted development, including benefits and limitations
  • Willingness to support on-call operations for system maintenance.

Responsibilities

  • Collect, model, and consolidate data for analytics, machine learning, and research
  • Design, build, and enhance data models and pipelines for reliability
  • Ensure high standards of data quality with engineering teams
  • Collaborate with product teams to deliver analytics to stakeholders
  • Manage the reliability and daily operations of the data platform.

Benefits

  • Eligible for equity
  • 99% employer paid health benefits (Medical, Dental, Vision) and One Medical subscription
  • 18 PTO days plus a holiday week
  • Monthly health and wellness budget
  • Company-sponsored retreats and social events
  • Sabbatical program available.
Full Job Description
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.

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 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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