Data Engineer, iOS — Health Technologies
Apple · San Diego, California, United States
Computers and Electronics Manufacturing · 10,001+ employees
About the role
Design and maintain data pipelines and analysis workflows for physiological sensing research. Develop iOS and macOS applications to support data collection and prototype new health features.
What they look for
Requirements
Requires a BS/MS in Computer Science or Engineering with 3+ years of software development experience. Must be expert in Python or Scala for large-scale data processing and proficient in Swift for Apple platform development.
Full description
Health Technologies is a unique cross-functional organization at Apple that works on inventing, researching, and validating new physiological sensing methods for Apple's current and future hardware platforms and software portfolio. We have an opportunity for a highly capable Data Engineer to join our multidisciplinary Software Team. You will integrate with our research study leads, data scientists, and engineers to design and support effective data pipelines and analysis workflows. Additionally, you will build and maintain the iOS and macOS apps that collect data and prototype new health features. This is a rare blend of data engineering rigor and Apple-platform app development, in service of research years ahead of product launch cycles.
Description
Work closely with team members and study staff to design, build, launch, and maintain systems for storing, aggregating, and analyzing large amounts of data.
Automate and monitor data ingestion and transformation pipelines, with hooks for QA, auditing, redaction, and compliance checks per data management specifications.
Process, troubleshoot, and clean incoming data from human studies; create and maintain databases with existing and incoming clinical data.
Architect data models and create tools to harmonize disparate data sources across wired and wireless collection paths.
Incorporate and comply with regulations as they pertain to electronic and clinical data and databases.
Design, develop, and maintain iOS and macOS apps (in Swift) that support data collection, data transfer, and health feature prototyping from research sensors and hardware.
Collaborate cross-functionally to understand data collection and consumption needs that support prototyping and research activities.
Share in our team's pride and sense of accountability to deliver high-quality, reliable, robust, secure, privacy-aware, and well-designed software, data systems, tools, and frameworks.
Enjoy and be comfortable working on new technologies in a research setting, years ahead of product launch cycles.
Minimum Qualifications
BS/MS in Computer Science, Engineering, Informatics, or equivalent 3+ years of experience in Software Development Expert in at least one of the following programming languages (Python or Scala), with hands-on experience in large-scale data processing using parallel computing (e.g., Apache Spark, Hadoop, Dask) and workflow orchestration and containerization (e.g., Airflow, Docker, Kubernetes) Experience designing and implementing custom ETL workflows and data models across relational and file-system databases (e.g., Postgres, SQL, Parquet, S3, Data Lake), harmonizing disparate data sources Experience in Swift and Xcode-based development, shipping iOS and macOS apps utilizing Apple technologies and frameworks (e.g. SwiftUI, SwiftData/CoreData, Swift Concurrency, Combine, HealthKit, Core Bluetooth)
Preferred Qualifications
Experience in Health/Wellness, Medical Device, or Biotech research or development, including biomedical sensors/platforms for measuring physiological signals Strong software engineering principles, including writing requirements and design documents, seeking and incorporating feedback, conducting code reviews, and championing software quality Proficient with modern AI coding agents and assistants (e.g., Claude Code, Cursor, Codex) and skilled at leveraging them to plan, design, develop, and test high-quality software efficiently Proficiency in Python frameworks and libraries for scientific computing (e.g., NumPy, Pandas, SciPy, PyTorch, PyArrow) Familiarity with AWS (or similar) cloud services and backend development Familiarity with machine learning development pipelines Knowledge of communication and data transfer protocols (e.g., TCP/IP, UDP, WebSocket, MQTT, Bluetooth/BLE, Serial/UART) Familiarity with working in Unix-type environments (Linux and macOS) Excellent written and verbal communication skills, with demonstrated technical leadership of software or data projects