Senior Data Engineer – Health Data Platform & ML

REGARD; Los Angeles (CA); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equity

Health benefits (Medical, Dental, and

PTO 18 days/yr

Wellness budget

Team retreat

Sabbatical

Job summary

Regard is seeking a Senior Data Engineer in the Los Angeles area to own the design, development, and deployment of data services powering our platform. You will optimize Spark workloads, model data, and ensure high-quality datasets for analytics, ML, and product use.

A hybrid work setup is offered with in-office days and relocation support if needed. You will collaborate with product and engineering teams on data architecture, scalability, and cost control, leveraging AWS tools, Iceberg,

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5+ years in data engineering roles.
• 3+ years with PySpark building data pipelines.
• 3+ years of public cloud experience (AWS S3/EMR/Athena).
• Strong Python and SQL proficiency.
• Hands-on data stack experience: modeling and pipelines.
• Experience with LLM-assisted development is a plus.
• Willingness for on-call operational support.

Responsibilities

• Collect, model, and consolidate data into the data platform for analytics, ML, and research.
• Design, build, and evolve data models and pipelines delivering data to downstream consumers.
• Own data quality and production readiness in collaboration with engineering teams.
• Partner with product to deliver analytics and actionable insights to stakeholders.
• Own reliability and day-to-day operations of the data platform and pipelines.

Skills

PySpark

Python

SQL

Data Modeling

Data Pipelines

AWS

On-call Support

Education

Bachelor's degree in Computer Science or related field

Tools

Apache Iceberg

Dagster

Clickhouse

PostgreSQL

FastAPI

Metabase

Job description

Regard is seeking a Senior Data Engineer in the Los Angeles area to own the design, development, and deployment of data services powering our platform. You will optimize Spark workloads, model data, and ensure high-quality datasets for analytics, ML, and product use.

A hybrid work setup is offered with in-office days and relocation support if needed. You will collaborate with product and engineering teams on data architecture, scalability, and cost control, leveraging AWS tools, Iceberg,