Senior Data Engineer - Healthcare Data (Hybrid, Equity)

Regard; California, Northern (MO, KY); Hybrid; USD 165,000 - 220,000; Full time

Benefits offered by this job

Equity

Relocation support

Hybrid work weeks with in-office weeks

Health benefits

PTO & holidays

Team retreats

Sabbatical program

Job summary

Regard is hiring a Senior Data Engineer to own the data services powering the Regard platform. You will ingest, standardize clinical data across health systems, and ensure reliable data for product and analytics workflows, including tuning Spark workloads and enforcing data quality.

The role emphasizes a transparent, code-driven data platform with collaboration across engineering, product, and analytics teams. Hybrid work in the US is supported with relocation assistance for in-office onboarding.

Qualifications

• Bachelor's degree in CS/Math/Stats or related field or equivalent
• 5+ years in data engineering roles
• 3+ years with PySpark to build data pipelines
• 3+ years with AWS tools (S3, EMR, Athena)
• Strong Python and SQL proficiency
• Hands-on data modeling and pipeline design
• Experience with LLM-assisted development and on-call support

Responsibilities

• Collect, model, and consolidate data into the data platform for analytics and research
• Design, build, and evolve data models and pipelines for downstream consumers
• Own data quality and production readiness across datasets
• Partner with product to deliver analytics and insights to stakeholders
• Maintain reliability of the data platform with proactive monitoring and operations

Skills

PySpark

Python

SQL

Data modeling

On-call support

Data pipelines

Analytics knowledge

Education

Bachelor's degree in CS/Math/Stats or equivalent

Tools

Apache Iceberg

Dagster

Clickhouse

PostgreSQL

FastAPI

Metabase

Job description

Regard is hiring a Senior Data Engineer to own the data services powering the Regard platform. You will ingest, standardize clinical data across health systems, and ensure reliable data for product and analytics workflows, including tuning Spark workloads and enforcing data quality.

The role emphasizes a transparent, code-driven data platform with collaboration across engineering, product, and analytics teams. Hybrid work in the US is supported with relocation assistance for in-office onboarding.