Health Research Data Engineer

At Apple, we want to make great products that empower people to improve their health. We are seeking an energetic and self-sufficient data engineer to join Apple's Health Research Data team to help us define, process, and manage the data used to improve existing health experiences, as well as create new ones. You will work with health research data, including data collected from the Apple Research app. As a member of our fast-paced group, you will not only have the unique and rewarding opportunity to accelerate upcoming features that will delight and inspire millions of Apple customers every day, but also contribute to applied health research by Apple and our academic partners.

We are seeking a data engineer to design and build robust data models and scalable data processing pipelines that transform complex health data. We need to reliably produce well-understood, easy-to-use datasets that can answer existing and future analytical questions. You will focus on core tools, frameworks, and patterns that will enable the whole team to meet our data quality and monitoring goals. If you believe the transformative power of data can only be fully harnessed when data management is treated as a first-class priority, this role was built for you.

In addition to using technical knowledge to drive features and improvements, you must be comfortable with rapidly evolving requirements and have excellent interpersonal skills. You will work closely with cross-functional partners across clinical, operational, product, legal, privacy, and engineering teams to gather requirements, design, implement, and manage studies through the collection, processing, and use of data. This is a high-impact, highly autonomous role for someone who pairs technical rigor with deep curiosity and an interest in making things better.

Design, develop, and maintain clean, production-grade data models and transformation pipelines that translate complex health data into reliable, scalable, easy-to-use, and well-documented analytical datasets. Use Spark to structure large volumes of data into tables, answer analytical questions, and investigate issues. Develop new frameworks and tools that help the team manage data parsing, processing, and quality. Participate in architecture and code reviews. Maintain a relentless focus on performance, usability, and quality. Communicate ideas and champion best practices within the team and to cross-functional partners. Work with subject matter experts to define data quality expectations for new data streams. Implement core data quality metrics and monitoring to track whether those expectations are being consistently met.

Bachelor's degree in Computer Science, Data Science, or a related field, or equivalent work experience. Enthusiasm for and experience working with data. Excellent programming skills in at least one of Scala, Java, or Python. Proficiency in SQL. Solid understanding of fundamental computer science concepts. Strong problem solver with meticulous attention to detail. Highly organized, creative, motivated, and passionate about achieving results. Excellent interpersonal skills and the ability to work well with other engineers by listening, communicating clearly, and actively sharing knowledge.

Hands-on experience with data modeling for large analytical workloads. Advanced SQL proficiency and experience with Python for data wrangling, exploratory data analysis, and building rich reports and dashboards. Experience with large-scale distributed processing engines, ideally Spark. Experience with Airflow or other modern data orchestration tools.