Remote Data Engineering Manager — Lead Pipelines & Teams

Mosaec; San Francisco (CA); On-site; USD 172,000 - 254,000; Full time

Benefits offered by this job

Medical/dental/vision

401k with match

Employee stock purchase plan

Family planning support

Parental leave

Life/AD&D/Disability

Generous time off

Wellness benefits

Job summary

Doximity is seeking a Senior Data Engineer and People Manager to lead data pipelines and ML-driven initiatives in a fast-growing healthcare technology environment. You will mentor a team, collaborate with product managers, and drive end-to-end data projects from conception to production.

Based in the US, you will join a distributed workforce with a strong emphasis on code quality, automated testing, and scalable data architectures while balancing hands-on work with leadership responsibilities.

Qualifications

• 5+ years of industry experience as a data engineer or similar role.
• Experience managing 3+ people, accountable for growth and success.
• Expert in Python with fluency in SQL and maintainable data pipelines.
• Experience creating automated testing and applying design patterns.

Responsibilities

• Collaborate with product managers, data analysts, and ML engineers to build pipelines and ETL tasks.
• Establish data architecture processes and standards for other teams.
• Participate in execution and planning of data team strategy.
• Collaborate with Data Leadership to ensure alignment and success across the organization.
• Manage Data Engineers to foster learning and growth.

Skills

Python

SQL

Data pipelines

Testing

Design patterns

ML/AI awareness

People management

Communication

End-to-end projects

Job description

Doximity is seeking a Senior Data Engineer and People Manager to lead data pipelines and ML-driven initiatives in a fast-growing healthcare technology environment. You will mentor a team, collaborate with product managers, and drive end-to-end data projects from conception to production.

Based in the US, you will join a distributed workforce with a strong emphasis on code quality, automated testing, and scalable data architectures while balancing hands-on work with leadership responsibilities.