Senior Software Engineer, Data

Doximity•San Francisco, CA

7d•Remote

About The Position

Doximity is the leading clinical AI company with the largest network of U.S. clinicians. Doximity's AI-powered workflow platform is trusted by over 85% of U.S. physicians and 300+ health systems. Doximity's mission is to help clinicians be more productive so they can provide better care for their patients. At Doximity, we value curiosity, ownership, inclusion, and a commitment to making a meaningful impact. If you're excited about solving complex problems that improve healthcare, we'd love to hear from you. Foremost a software engineer. You exemplify high code quality and guide others, and have at least 5 years of industry experience as a data engineer or similar role. You are experienced in creating automated testing, applying design patterns, and other engineering best practices. You are an expert in Python and possess fluency in SQL and have developed maintainable data pipelines with each. Hands-on with architecting solutions. You have designed several data pipelines from start to finish. Choosing appropriate technologies, building, testing and rollout. Experience with asynchronous systems. You are comfortable identifying and applying APIs, streaming, multithreading, and other asynchronous approaches to the right problems. You understand how to monitor and maintain these systems. Product mindset. You think about the business impact of your work, and can use high-level goals to prioritize work. Communication Extraordinaire. You excel at communicating to both technical and non-technical people, with an ability to explain complex concepts simply. ML/AI–aware. You have working knowledge of how ML/AI applications are deployed and monitored, and you’re motivated to use this awareness to advance data-driven initiatives.

Requirements

At least 5 years of industry experience as a data engineer or similar role.
Expertise in Python.
Fluency in SQL.
Experience in creating automated testing.
Experience applying design patterns and other engineering best practices.
Experience designing several data pipelines from start to finish, including choosing appropriate technologies, building, testing, and rollout.
Experience with asynchronous systems (APIs, streaming, multithreading).
Understanding of how to monitor and maintain asynchronous systems.
Ability to think about the business impact of work and use high-level goals to prioritize.
Ability to communicate complex concepts simply to both technical and non-technical people.
Working knowledge of how ML/AI applications are deployed and monitored.
Motivated to use ML/AI awareness to advance data-driven initiatives.

Nice To Haves

High code quality and ability to guide others.

Responsibilities

Collaborate with product managers, data analysts, and machine learning engineers to develop pipelines and ETL tasks in order to facilitate the extraction of insights.
Understand product requirements and translate them into actionable project plans that you or your peers execute upon.
Establish data architecture processes and practices that can be scheduled, automated, replicated and serve as standards for other teams to leverage.
Collaborate with your team's Data Leadership to identify and push forward meaningful projects across the commercial org.