Data Engineer, Health Sensing

Apple Inc

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Quick summary

Work type
On-site
Location
Sunnyvale, CA
Salary
$150,400–$277,600 / yr
Posted
48 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $169k
This role $214k
$108k $296k
below market most similar roles pay here above market

This role pays more than 81% of similar roles. Most pay $126,800–$211,200 — the blue band above. At the midpoint, this role pays about $214k versus about $169k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3564 open roles on FindRole.

Listed pay typically runs $166,600–$277,600 across 2760 roles with salary data.

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At a glance

TL;DR · Data Engineer, Health Sensing

The Data Engineer - Health Sensing joins a team of data engineers building scalable infrastructure to power health research. In this role, you will design and develop high-throughput, distributed data pipelines to ingest, process, and transform large volumes of time-series sensor data from health studies. You will implement robust ETL pipelines, build visualization tools and dashboards, and drive data architecture standardization to support evolving research needs. The position requires proficiency in Python, SQL, and distributed computing frameworks like Apache Spark. You will work with binary and proprietary data formats to support clinical validations and advanced analytics. Key technical skills include data modeling, experience with containerization tools like Docker and Kubernetes, and familiarity with job orchestration tools such as Apache Airflow within Linux-based environments.

What does a Data Engineer earn in California?

Median $187700 from 43 postings across 23 companies.

See salary data

What you'll do

  • Design and develop scalable, parallelized data systems to process complex time-series health data from sensors.
  • Implement robust ETL pipelines using Apache Spark to ingest and transform binary and proprietary data formats.
  • Gather requirements from study stakeholders to ensure data architecture supports evolving research needs.
  • Build tools and dashboards to visualize health data and support research insights.
  • Support the design, integration, testing, and deployment of health data solutions with cross-functional teams.
  • Drive standardization and reusability across studies to evolve the company-wide health data platform.

What we're looking for

  • 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 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 with sensor data, time-series data, or healthcare datasets (preferred).
  • Experience with cloud environments, containerization tools like Docker and Kubernetes, or job orchestration tools like Apache Airflow (preferred).

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