The role is for a Data Engineer on a team that builds scalable data infrastructure to support health research at Apple. The team focuses on developing high-performance data pipelines and processing systems for large-scale health studies and analytics. The engineer will design and build distributed data pipelines to process sensor data, contributing to health research and product development. Collaboration with researchers and cross-functional teams is essential to ensure data accuracy and accessibility.

• BS degree in Computer Science, Engineering, Data Science, or a related technical field.
• Minimum of 3 years relevant industry experience building and maintaining data pipelines or distributed data systems.
• Proficiency in Python and strong programming skills with a focus on writing clean, maintainable, and high-performance code.
• Familiarity in SQL for querying, transforming, and analyzing structured data.
• Hands-on experience with distributed computing frameworks like Apache Spark.
• Experience with ETL development, data modeling, and data transformation workflows.
• Experience working with sensor data, time-series data, or healthcare datasets.
• Experience working in cloud-based environments (e.g., AWS, GCP, or Azure) and with containerization tools like Docker and Kubernetes.
• Familiarity with job orchestration tools such as Apache Airflow or similar workflow schedulers.
• Comfort working in Linux-based environments, including scripting, system navigation, and basic troubleshooting.
• Exposure to clinical studies, FDA validation processes, or working in regulated health environments.
• Strong communication and collaboration skills; ability to work cross-functionally with technical and non-technical partners.

• Design and develop scalable, parallelized data systems to process complex, time-series health data captured from consumer-grade sensors.
• Implement robust ETL pipelines using distributed computing frameworks such as Apache Spark to ingest and transform binary and proprietary data formats.
• Collaborate with study stakeholders to gather requirements and contribute to the study design process, ensuring data architecture supports evolving research needs.
• Build tools and dashboards to visualize health data and support data exploration, analysis, and research insights.
• Work closely with cross-functional teams including Software, Algorithms, and Quality Engineering to support design, integration, testing, and deployment of health data solutions.
• Own and evolve data architecture by driving standardization and reusability across studies, contributing to the development of a company-wide health data platform.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.