Senior Software Engineer, AI-Driven Data Pipelines - Remote

Doximity; San Francisco, Northern (CA, KY); Hybrid; USD 165,000 - 221,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) match

Flexible PTO

Parental leave

Professional development

Wellness resources

Remote stipend

Job summary

Doximity is seeking a software engineer focused on data engineering to build and maintain robust data pipelines and testing practices. You will design end-to-end data solutions, work with APIs and asynchronous systems, and partner with product managers and ML engineers to extract scalable insights.

Location is remote in the United States, Canada, or some countries in South America. The role emphasizes a product mindset, strong communication, and awareness of ML/AI deployment.

Qualifications

• 5+ years data engineer or similar role.
• Experience in creating automated testing, applying design patterns, and other engineering best practices.
• Expert in Python and fluent in SQL with maintainable data pipelines.

Responsibilities

• Collaborate with product managers, data analysts, and ML engineers to develop pipelines and ETL tasks.
• Translate product requirements into actionable project plans.
• Establish data architecture processes and practices that can be automated and reused across teams.
• Collaborate with Data Leadership to push meaningful projects across the org.
• Manage over 500 private repositories containing pipelines and internal tools.

Skills

Python

SQL

Data pipelines

Automated testing

Design patterns

Job description

Doximity is seeking a software engineer focused on data engineering to build and maintain robust data pipelines and testing practices. You will design end-to-end data solutions, work with APIs and asynchronous systems, and partner with product managers and ML engineers to extract scalable insights.

Location is remote in the United States, Canada, or some countries in South America. The role emphasizes a product mindset, strong communication, and awareness of ML/AI deployment.