Senior Software Engineer, Data Job at Doximity, San Francisco, CA

  • Doximity
  • San Francisco, CA

Job Description

About Doximity 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. About the Role - 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 aychronous 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. Location : This role is remote in the United States, Canada, or some countries in South America. Here's How You Will Make an Impact - 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. About Us - Explore our stack - We have over 500 private repositories in Github containing our pipelines, our own internal multi-functional tools, and open-source projects - We have worked as a distributed team for a long time; we're currently about 65% distributed - Find out more information on the Doximity engineering blog - Our company core values - Our recruiting process - Our product development cycle - Our on-boarding & mentorship process Compensation The anticipated total compensation for this role is $165,000 - $221,000, depending on factors such as experience, skills, location, and internal equity. Our total compensation package may include: - Base salary - Equity (where applicable) - Annual bonus or incentive compensation (where applicable) Specific compensation details will be discussed during the interview process. Benefits In addition to competitive compensation, Doximity offers a comprehensive benefits package for full time employees. Some of our offerings include: - Medical, dental, and vision insurance - 401(k) with company match - Flexible paid time off and company holidays - Paid parental leave - Professional development and learning opportunities - Wellness and mental health resources - Remote work support and home office stipend (where applicable) Why You'll Love Working Here At Doximity, you'll join a mission-driven company where your work has a meaningful impact on healthcare.

Job Tags

Full time, Work from home, Home office, Flexible hours

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