Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.
We value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare. Our data team is deliberate and self-reflective about the kind of team and culture that we are building, seeking data engineers and scientists that are not only strong in their own aptitudes but care deeply about supporting each other’s growth. We have one of the richest healthcare datasets in the world, and our team brings a diverse set of technical and cultural backgrounds.
You will join out team of data analysts, scientists, and engineers to build and maintain ETL and ML pipelines with focus on scalability and performance, particularly around Spark.
How you’ll make an impact:
- 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.
What we’re looking for:
- 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.
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