Senior Data Engineer - AI Healthcare Platform

Rad AI; San Francisco (CA); Hybrid; USD 145,000 - 200,000; Full time

Benefits offered by this job

Medical, Dental, Vision & Life

HSA with employer match

401(k)

Paid holidays

Flexible PTO

Equipment stipend

Job summary

Rad AI is hiring a Senior Data Engineer to design and maintain a scalable data platform, pipelines, and management tools. You will collaborate with researchers and engineers to meet data needs for model training, monitoring, and production, while ensuring data quality, security, and governance.

The role requires 5+ years in data engineering, experience with distributed pipelines and big data tech, and hands-on work with SQL/NoSQL databases.

Qualifications

• 5+ years of experience in data engineering.
• Experience designing distributed data pipelines with big data technologies.
• Hands-on experience building scalable data infrastructure; IaC like Terraform.
• Experience with SQL and NoSQL databases (DynamoDB, ElasticSearch, PostgreSQL).
• Prior software engineering experience is a plus.

Responsibilities

• Design and implement scalable data architectures and pipelines.
• Maintain data quality, security, and governance across platforms.
• Collaborate with researchers and stakeholders on data needs and models.
• Own data engineering projects from design to deployment.
• Evaluate data technologies to improve efficiency and reliability.
• Develop and enforce standards for a high-scale data platform.

Skills

Data engineering

Distributed data pipelines

Big data technologies

SQL

NoSQL databases

Terraform

Software engineering

Tools

DynamoDB

ElasticSearch

PostgreSQL

Job description

Rad AI is hiring a Senior Data Engineer to design and maintain a scalable data platform, pipelines, and management tools. You will collaborate with researchers and engineers to meet data needs for model training, monitoring, and production, while ensuring data quality, security, and governance.

The role requires 5+ years in data engineering, experience with distributed pipelines and big data tech, and hands-on work with SQL/NoSQL databases.