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Benefits & Perks
•Healthcare
•401(k)
•Equity
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•Healthcare
•401k
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Required Skills
Site Reliability Engineering
Cloud infrastructure
Kubernetes
Data systems
Distributed systems
Apache Spark
Apache Flink
Apache Kafka
AWS
Automation
Infrastructure as Code
At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses.
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone.
Description:
As a Data Site Reliability Engineer in Apple Ads, you will focus on designing, building, and managing cloud-based systems and infrastructure that stores, process, transforms and analyzes large datasets. You will ensure data and corresponding infrastructure is accessible, reliable, and secure within the cloud environment, working with various Apple Internal and 3rd party cloud providers like AWS.","responsibilities":"Your high-level responsibilities will include:
Design, build and manage large scale distributed data systems on AWS using services such as EMR, EKS, MSK.
Design and develop internal tooling and automation frameworks to improve data infrastructure reliability, cost-efficiency, and operational visibility.
Collaborate with cross-functional engineering teams like advertising, machine learning and data platforms to define infrastructure architecture, troubleshoot complex issues, and drive production excellence.
Lead initiatives to eliminate toil via automation, improve efficiency and scalable deployment patterns.
Contribute to strategic decision making related to adoption of a multi-cloud echo system to maintain operational excellence on the current stack while still enabling the path for future innovation.
Preferred Qualifications:
Proven experience as a committer to open-source projects like Apache Spark, Flink, etc
Track record of driving automation, cost optimization and performance tuning at scale for data systems.
Experience leveraging ML and GenAI capabilities to improve infrastructure and Operational efficiency is a plus.
Experience driving adoption of new technologies and influencing designing of systems.
Strong programming skills on object-oriented, functional or procedural programming languages, preferably Java / Scala / Kotlin / Python
Experience designing and managing Infrastructure as Code with Helm and CRD, ensuring repeatable, secure, and scalable deployments.
Minimum Qualifications:
5+ years of experience in Site Reliability Engineering with a strong focus on building, scaling and operating cloud based distributed data systems.
Proven expertise running cloud infrastructure built on managed services offered by cloud providers like AWS
Strong technical grasp and experience working on Open Source technologies designed for large scale data processing, like Apache Spark, Flink, Kafka, Iceberg, etc.
Big Data processing and storage systems (streaming and batch)
Strong expertise and experience with container orchestration systems like Kubernetes
Experience designing, analyzing and troubleshooting large-scale distributed systems.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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. Learn more about your EEO rights as an applicant .
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 $147,400 and $272,100, 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.
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
L2
L3
L4
L5
L6
L2 · Cybersecurity Analyst L2
0 reports
$169,000
total / year
Base
$67,600
Stock
$84,500
Bonus
$16,900
$118,300
$219,700
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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