{"id":4066702,"url":"https://alion.io/job/apple-data-engineer-health-sensing","title":"Data Engineer - Health Sensing","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":90,"open_postings":824,"ghost_share":0,"stale_share":0.214,"repost_share":0.006,"time_to_fill_p50_days":122,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"Airflow","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"Linux","optional":true}],"status":"live","first_seen_at":"2025-04-30T20:56:08Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T11:32:14Z","board_verified":true,"closed_at":null,"days_open":559,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":559},"description":"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.\nDescription\nWe 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.\n- Design and develop scalable, parallelized data systems to process complex, time-series health data captured from consumer-grade sensors.\n- Implement robust ETL pipelines using distributed computing frameworks such as Apache Spark to ingest and transform binary and proprietary data formats.\n- Collaborate with study stakeholders to gather requirements and contribute to the study design process, ensuring data architecture supports evolving research needs.\n- Build tools and dashboards to visualize health data and support data exploration, analysis, and research insights.\n- Work closely with cross-functional teams including Software, Algorithms, and Quality Engineering to support design, integration, testing, and deployment of health data solutions.\n- Own and evolve data architecture by driving standardization and reusability across studies, contributing to the development of a company-wide health data platform.\nMinimum Qualifications\nBS degree in Computer Science, Engineering, Data Science, or a related technical field.\nMinimum of 3 years relevant industry experience building and maintaining data pipelines or distributed data systems.\nProficiency in Python and strong programming skills with a focus on writing clean, maintainable, and high-performance code.\nFamiliarity in SQL for querying, transforming, and analyzing structured data.\nHands-on experience with distributed computing frameworks like Apache Spark.\nExperience with ETL development, data modeling, and data transformation workflows.\nPreferred Qualifications\nExperience working with sensor data, time-series data, or healthcare datasets.\nExperience working in cloud-based environments (e.g., AWS, GCP, or Azure) and with containerization tools like Docker and Kubernetes.\nFamiliarity with job orchestration tools such as Apache Airflow or similar workflow schedulers.\nComfort working in Linux-based environments, including scripting, system navigation, and basic troubleshooting.\nExposure to clinical studies, FDA validation processes, or working in regulated health environments.\nStrong communication and collaboration skills; 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