As a Data Engineer, you will help build and maintain the data infrastructure that powers our data-driven solutions, ultimately enhancing the healthcare experience for millions of patients and healthcare providers. You’ll work closely with our Senior Data Engineer and cross-functional partners, with direct mentorship and opportunities to develop your skills across the full data engineering lifecycle. If you're excited about the intersection of data engineering and machine learning, this role offers a clear path to grow in that direction. Ideal candidates will possess a high degree of user empathy and a focus on the quality and speed of our product. Our patients simply can’t afford to wait!

This job posting is for an existing vacancy. The salary range for this position is $100,000 – $130,000 annually, depending on the experience and expertise you bring to the team. Salary is just one part of the story, though; this role is also eligible for equity in the form of stock options and includes a comprehensive health and benefits package. We view our compensation as a total investment in your well-being, designed to support you both in your work and in your life outside of it.

In this role you will:

• Build and maintain data models and transformation workflows that support analytics, reporting, and product use cases.
• Support the development and improvement of data pipelines and systems to process and analyze healthcare data, gaining experience across the full data engineering lifecycle from ingestion and transformation to storage and consumption.
• Work with Python and SQL to transform, validate, and troubleshoot data across our platform.
• Contribute to our Databricks-based analytics platform and help improve the usability, quality, and documentation of our datasets.
• Collaborate with cross-functional teams to understand their data needs and contribute to our data infrastructure roadmap.
• Gain hands-on exposure to machine learning workflows - from data preparation and feature engineering to model training - with room to grow deeper as the team and your skills evolve.

What you’ll need to be successful:

• 1–2 years of engineering experience in data engineering, analytics engineering, software engineering, or a related field, including strong internship or co-op experience.
• Bachelor’s degree in Software Engineering, Computer Science, or a related field, or equivalent practical experience.
• Strong fundamentals in Python and SQL.
• Hands-on experience working with structured data in an internship, research, academic, or early-career industry setting.
• Strong problem-solving skills and attention to detail, with a focus on delivering high-quality solutions.
• A collaborative mindset, strong communication skills, and eagerness to learn in a fast-paced environment.

Nice to have:

Exposure to Databricks or similar modern data platforms.
Practical exposure to machine learning concepts such as model training, feature engineering, or evaluation.