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.

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.

Data Engineer

Key skills