Data Engineering Manager

Job Overview

What You’ll Do

• Collaborate with product managers, data analysts, and machine learning engineers to develop data pipelines and ETL tasks that support the extraction of useful insights.
• Establish data architecture processes and engineering practices that can be scheduled, automated, replicated, and adopted as standards by other teams.
• Work with product leaders and managers to help inform data team strategy.
• Actively participate in the execution and planning of organizational data initiatives.
• Collaborate with Doximity’s Data Leadership team to maintain alignment across the broader Data Organization.
• Manage individual Data Engineers and support their learning, professional growth, and success.
• Contribute technically as a hands-on engineer while also fulfilling management and mentoring responsibilities.
• Help teams maintain strong engineering practices across data pipelines, architecture, testing, and development.

What Doximity Is Looking For

• At least 5 years of industry experience working as a Data Engineer or in a similar engineering role.
• Strong commitment to high-quality code and the ability to guide other engineers toward strong engineering standards.
• Expert-level Python skills.
• Fluency in SQL.
• Experience developing maintainable data pipelines using Python and SQL.
• Experience creating automated tests and applying design patterns and other engineering best practices.
• Previous people-management experience overseeing at least three people and being accountable for their individual and team development.
• Strong written and verbal communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Ability to operate as a player-coach, balancing individual technical contribution with management and mentorship responsibilities.
• Experience leading projects through the full lifecycle, including idea generation, planning, execution, and delivery.
• Working knowledge of how machine learning and AI applications are deployed and monitored.
• Interest in applying ML/AI awareness to advance data-driven initiatives.

Technical Focus

• Python
• SQL
• ETL workflows
• Maintainable data pipelines
• Data architecture
• Automated testing
• Engineering design patterns
• Machine learning and AI application awareness
• Data-driven product development
• Engineering standards and reusable processes

Engineering Leadership

This position is designed for someone who remains an engineer while taking responsibility for the development and success of other engineers. The successful candidate should be comfortable moving between hands-on technical contribution, project leadership, mentoring, strategic collaboration, and people management.

You will work closely with Doximity’s wider Data Organization while helping individual Data Engineers grow and establishing practices that can improve how data work is delivered across teams.

Compensation

The stated U.S. total compensation range for this full-time position is $172,000 to $254,000, inclusive of salary and equity.

Doximity determines individual compensation based on factors including relevant skills, experience, education, and training. The stated compensation range does not include employee benefits.

Benefits & Perks

• Medical, dental, and vision offerings for employees and their families.
• 401(k) with matching program.
• Employee stock purchase plan.
• Family planning support.
• Childcare FSA.
• Parental leave.
• Life insurance.
• AD&D coverage.
• Disability coverage.
• Generous time off.
• Company holidays.
• Paid company trips.
• Wellness benefits.

About Doximity

Doximity develops a digital platform for U.S. medical professionals with a mission to help physicians become more productive and provide better care for their patients.

The platform enables verified clinician members to collaborate with colleagues, stay informed about medical news and research, manage their careers, and conduct virtual patient visits.

Doximity also operates a substantial engineering environment, including more than 500 private GitHub repositories containing data pipelines, internal tools, and open-source projects. The company has experience operating as a distributed organization and states that approximately 65% of its team is distributed.

Who This Role May Suit

This opportunity may be particularly relevant for an experienced Data Engineer who has progressed into people management but still wants to remain technically involved. Candidates should be comfortable owning projects end-to-end, mentoring engineers, collaborating across data and product functions, and maintaining strong standards around Python, SQL, data pipelines, testing, and architecture.