The Health Technologies Team conceives and proves out innovative technology for Apple's future products and features in health. We have an opportunity for a highly capable Data Engineer to join a multi-disciplinary team. You will have the opportunity to integrate with our research study leads, data scientists and engineers to develop and support effective data analysis and machine learning workflows.
Typically requires 5+ years of experience in software development.
Expert in at least one of the following programming languages: (Python, Scala, Java).
Expert in large-scale data processing using parallel computing (e.g. Apache Spark, Hadoop, Dask).
Workflow orchestrations (e.g., Airflow, Luigi).
Proficiency in the Python programming language.
Proficiency in Python frameworks and libraries for scientific computing (e.g. Numpy, Pandas, SciPy, Pytorch, Pyarrow).
Designing and maintaining relational and file system databases (e.g. Postgres, SQL, Parquet, S3, Data Lake).
Great understanding of infrastructure designs.
In depth experience working with enterprise DE tools and the ability to learn and improve upon in-house DE tools.
Experience designing and implementing custom ETL workflows.
Demonstrated technical leadership and good communication skills.
You will work closely with team members and study staff to design, build, launch and maintain systems for storing, aggregating and analyzing large amounts of data. Process, troubleshoot, and clean incoming data from human studies. Automate and monitor data ingestion and transformation pipelines, with hooks for QA, auditing, redaction and compliance checks per data management specifications. Create and maintain databases with existing and incoming clinical data. Architect data models and create tools to harmonize disparate data sources. Incorporate and comply with regulations as they pertain to electronic and clinical data and databases.
Education & Experience
Education & Experience
BS/MS in Computer Science, Engineering, Informatics, or equivalent
The following experience is considered a plus:
Experience with biomedical sensors/platforms for measuring physiological signals in the health, wellness and/or fitness realm.
Familiarity with best practices for information security, including safe harbor privacy principles for sensitive data.
Experience with machine learning development pipelines.
Experience with data modeling of diverse types of data streams.
Familiarity with AWS (or similar) cloud services and backend development.
Familiarity with development on Linux and MacOS.
Familiarity with iOS and WatchOS frameworks and app development.
Pay & Benefits
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $102,000.00 and $212,200.00, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.