채용
We are seeking pragmatic Data Product Engineering Lead to join a team passionate about creating analytic experiences that simplify data into insights and catalyze decision making. The WPC Data Science and Analytics Engineering team collaborates with a wide variety of partners within Apple to optimize user experience and systems efficiency across Apple Services Payments & Commerce lines of business.
Description
The job is cross-functional and requires making sense of Internet-scale data across numerous product, engineering and customer touch points. It requires fluency using statistics, data modeling and modern interactive visualizations to answer specific questions, design thinking about personas and data schemas, data and ml pipelines, data visualization skills, and most importantly, a passion for creating scalable analytics strategies to communicate actionable insights and intuitive decision tools to all levels of the company.","responsibilities":"In this role, you will:
Instrument APIs, user journey and interaction flows to systematically collect behavioral, transactional, and operational data, enabling robust analytics and insightful reporting
Design, develop, and maintain scalable analytical data products and architectures for Payments & Commerce products.
You will help design and build solid metric foundation layer that will be fundamental to drive trustable insights and machine learning predictive/forecasting and AI driven inferences
Optimize data workflows and pipelines to enhance data processing efficiency and reliability.
Collaborate closely with diverse set of partners to gather requirements, prioritize use cases, and ensure high-quality data products delivery.
Preferred Qualifications
Experience authoring technical and instrumentation specs, and working with APIs and message schemas (MSDs).
Proven ability to design reusable frameworks, tools, and automation to accelerate platform adoption.
Hands-on experience with distributed querying (Trino), real-time analytics (OLAP), near-real-time processing (NRT), and data mesh architectures.
Familiarity with Generative AI/LLM applications for test generation, anomaly detection, documentation automation, and privacy-safe synthetic data creation.
Proven experience building data quality frameworks (validation, profiling, anomaly detection, synthetic data generation).
Track record of independent problem-solving, sound technical judgment, and delivering impactful results at scale.
Minimum Qualifications
Bachelor's or Master's degree in Computer Science or a related technical field or equivalent experience
8+ years of experience in designing, developing and deploying next-gen Analytical Data Products leveraging data with Data Visualizations, ML & AI pipelines preferably for a digital subscription business
Strong proficiency in SQL, Scala, Python, or Java, with hands-on experience in data pipeline tools (e.g., Apache Spark, Kafka, Airflow), CI/CD practices, and version control.
Proficiency with cloud platforms (AWS, Azure, GCP) and data management and analytics tools like Snowflake, Databricks and Tableau or other visualization tools.
Strong understanding of data warehousing, data modeling (dimensional/star schemas), and metric standardization.
Excellent problem-solving and analytical skills, with the ability to influence stakeholders and drive adoption of best practices.
Experience leading discovery workshops with domain experts and synthesizing requirements into wireframes, mockups and development specifications.
You have good communication, social and presentation skills with meticulous attention to detail.
Strong time management skills with the ability to handle work to tight deadlines and the pressure of executive requests over multiple projects.
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 $181,100 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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Apple 소개

Apple
PublicApple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.
10,001+
직원 수
Cupertino
본사 위치
$3.5T
기업 가치
리뷰
3.9
10개 리뷰
워라밸
2.5
보상
4.2
문화
3.8
커리어
3.5
경영진
3.2
72%
친구에게 추천
장점
Great benefits and compensation
Talented colleagues and supportive teams
Learning opportunities and mentorship
단점
Work-life balance challenges
High stress and pressure
Fast-paced environment
연봉 정보
11,365개 데이터
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0개 리포트
$114,215
총 연봉
기본급
$45,686
주식
$57,108
보너스
$11,422
$79,951
$148,480
면접 경험
3개 면접
난이도
3.3
/ 5
소요 기간
28-42주
합격률
33%
경험
긍정 33%
보통 0%
부정 67%
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
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