- Collaborate with data scientists to develop ML pipelines that can perform at scale.
- Understanding of tools and processes required to support live models.
- Establish data architecture processes and practices that can be scheduled, automated, replicated and serve as standards for other teams to leverage.
- Collaborate with data analysts to develop ETL pipelines tasks in order to facilitate extraction of insights from data.
- Spearhead, plan and carry out the implementation of solutions while self-managing.
- At least three years of professional experience developing data infrastructure solutions.
- Fluency in Python and understanding of Object Oriented Programming.
- In-depth experience building scalable solutions in PySpark.
- In-depth expertise with Spark and EMR in order to tweak cluster for optimum performance.
- Passion for clean code and testing with Pytest, FactoryBoy, or equivalent.
- Astute ability to self-manage, prioritize, and deliver functional solutions.
- Working knowledge of Unix, Git, and AWS tooling.
- B.S. in Computer Science is a nice to have but we love professional experience even more than a degree.
We’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!