Start Date
Immediate
Expiry Date
01 Dec, 25
Salary
272100.0
Posted On
01 Sep, 25
Experience
3 year(s) or above
Remote Job
Yes
Telecommute
Yes
Sponsor Visa
No
Skills
Structured Data, Apache Spark, Sql, Scripting, Computer Science, Data Systems, Python, Data Science, Docker, Data Modeling, Kubernetes
Industry
Information Technology/IT
We are a team of strong data engineers that build the scalable data infrastructure that powers health research at Apple. We develop high-performance data pipelines and processing systems to support large-scale health studies, clinical validations, and advanced analytics. Working closely with researchers, clinicians, and product teams, we ensure health data is accurate, accessible, and actionable - enabling science and product innovation that can improve lives.
DESCRIPTION
We are looking for a passionate and experienced Data Engineer to join our team focused on powering cutting-edge health research through scalable and reliable data systems. In this role, you’ll design and build high-throughput, distributed data pipelines that ingest, process, and transform large volumes of sensor data collected from health studies. Your work will directly contribute to the advancement of health research and product development at Apple. - 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.
MINIMUM QUALIFICATIONS
PREFERRED QUALIFICATIONS
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