Senior Data Engineer – Healthcare AI (Remote/Hybrid)

Rad AI; United States; Hybrid; USD 140,000 - 180,000; Full time

Benefits offered by this job

Health insurance

HSA with employer match

401(k)

Paid holidays

Flexible PTO

Equipment stipend

Job summary

Rad AI is hiring a Senior Data Engineer to build and maintain a scalable data platform for healthcare AI. You will design architectures, pipelines, and data products, working with researchers to meet analytic and model-training needs.

Join a fast-growing startup focused on transforming radiology with AI, building robust data tooling, and ensuring data quality, security, and scalability across large datasets.

Qualifications

• 5+ years of experience in data engineering.
• Experience designing distributed data pipelines for large-scale datasets.
• Hands-on experience building reliable, scalable data infrastructure.
• Proficiency with SQL and NoSQL databases (e.g., AWS DynamoDB, Elasticsearch, PostgreSQL).
• Experience using Terraform for IaC and data platform tooling.

Responsibilities

• Design and implement scalable data architectures and pipelines.
• Define internal standards for style, maintenance, and best practices on a high-scale data platform.
• Collaborate with researchers to understand data needs for model training and monitoring.
• Own data engineering projects end-to-end from design to deployment.
• Ensure data quality, security, and access controls across platforms.
• Evaluate new data technologies to improve efficiency and reliability.

Skills

Data engineering

Distributed pipelines

Big data

SQL

NoSQL

Terraform IaC

Software engineering

Tools

Apache Airflow

AWS Glue

Spark

Terraform

DynamoDB

Elasticsearch

PostgreSQL

Job description

Rad AI is hiring a Senior Data Engineer to build and maintain a scalable data platform for healthcare AI. You will design architectures, pipelines, and data products, working with researchers to meet analytic and model-training needs.

Join a fast-growing startup focused on transforming radiology with AI, building robust data tooling, and ensuring data quality, security, and scalability across large datasets.