Senior Data Engineer - AI Pipelines (Remote)

Doximity; Plano (TX); On-site; USD 165,000 - 221,000; Full time

Benefits offered by this job

Equity

Annual bonus

Medical insurance

401(k)

PTO & holidays

Parental leave

Dev opportunities

Wellness resources

Remote work stipend

Job summary

Doximity is seeking a software engineer with a data-engineering focus to join our remote U.S.-based team. Bring 5+ years in data engineering or a similar role, strong Python skills, and fluency in SQL to build and maintain scalable data pipelines.

You will design, test, and ship end-to-end data solutions, apply best practices, and work with asynchronous systems, APIs, streaming, and multithreading while staying ML/AI aware to drive data-driven initiatives.

Qualifications

• At least 5 years of industry experience as a data engineer or similar role.
• Fluent SQL and strong Python skills.
• Experience designing and maintaining end-to-end data pipelines.
• Familiar with automated testing and software design patterns.
• Knowledge of asynchronous systems, APIs, streaming and multithreading.

Responsibilities

• Collaborate with product managers, data analysts, and ML engineers to develop pipelines and ETL tasks.
• Translate product requirements into actionable project plans for delivery.
• Establish scalable data architecture processes and standards for reuse.
• Partner with Data Leadership to drive meaningful projects across the commercial org.
• Leverage large repositories and internal tools to support data workflows.

Skills

Python

SQL

Data pipelines

Testing

Design patterns

Async systems

APIs

Streaming

Multithreading

ML/AI awareness

Product mindset

Communication

Job description

Doximity is seeking a software engineer with a data-engineering focus to join our remote U.S.-based team. Bring 5+ years in data engineering or a similar role, strong Python skills, and fluency in SQL to build and maintain scalable data pipelines.

You will design, test, and ship end-to-end data solutions, apply best practices, and work with asynchronous systems, APIs, streaming, and multithreading while staying ML/AI aware to drive data-driven initiatives.