below marketmost similar roles pay hereabove market
This role pays more than
91%
of similar roles. Most pay
$128,005–$215,000
— the blue band above.
At the midpoint, this role pays about
$255k
versus about
$172k
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
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
The Sr Data Engineer, AIML joins the AI and Machine Learning team to build world-class data infrastructure and solutions powering the Apple Foundation Model lifecycle. This role involves designing, building, and maintaining scalable data pipelines, platforms, and integration solutions to enable reliable analytics, machine learning, and business intelligence. The engineer will develop large-scale batch and streaming pipelines, manage data models, and ensure data quality, lineage, and governance across internal and external systems. Key technologies include Python, Google Cloud Platform services like BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, and Composer, along with Spark-based processing. The position requires expertise in ETL/ELT workflows, event-driven architectures, and MLOps workflows, including feature engineering and training data generation for generative AI and LLM-based systems.
What does a Data Engineer earn in California?
Median $187700 from 41 postings across 21 companies.
Design, build, and optimize large-scale batch and streaming data pipelines using Google Cloud Dataflow.
Develop and maintain data models and transformations in BigQuery to support analytics and ML use cases.
Build scalable data architectures using GCP services including Pub/Sub, Dataflow, and Cloud Storage.
Integrate data from internal and external systems while ensuring data quality, lineage, and governance.
Develop robust ETL/ELT workflows and orchestration pipelines using cloud-native tooling.
Monitor, troubleshoot, and optimize data pipelines for performance, cost efficiency, and reliability.
Implement best practices for data security, access control, and compliance in cloud environments.
What we're looking for
Minimum 10+ years of experience in data engineering, backend engineering, or distributed systems.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
Hands-on experience designing and building large-scale batch and streaming data pipelines using Python and distributed systems.
Expertise in ETL/ELT development, event-driven architectures, and high-volume datasets using Pub/Sub, Dataflow (Apache Beam), and Spark-based processing.
Deep expertise in Google Cloud Platform data ecosystem including BigQuery, Dataflow, Pub/Sub, and Composer.
Proficiency in version control, CI/CD practices, testing, and code reviews.
7+ years of experience in data engineering or large-scale distributed systems (preferred).
Experience supporting ML pipelines, MLOps workflows, and Generative AI/LLM-based systems (preferred).
Swift
Go
C++
Java
Python
Rust
React
Angular
Vue
JavaScript
Objective-C
AWS
Google Cloud
Microsoft Azure
Kubernetes
Spark
Hadoop
Kafka
SQL
NoSQL
Data Pipelines
Distributed Systems
iOS
Android
macOS
visionOS
watchOS