Jobs
Benefits & Perks
•401(k) matching
•Comprehensive health, dental, and vision insurance
•Competitive salary and equity package
•Professional development budget
•Flexible work arrangements
•Generous paid time off and holidays
•Healthcare
•Equity
•Learning
•Flexible Hours
Required Skills
React
Node.js
JavaScript
About the Role
Are you a Technical Product Leader passionate about building data products that empower Data Scientists and Engineers? Do you excel at bridging technical architecture with product strategy to unlock the full potential of data? At Apple, we turn innovative ideas into groundbreaking products and services at an incredible pace. Join us and play a critical role in shaping the future of data-driven decision-making!
Our Data Science & Analytics team is dedicated to enhancing customer experiences, accelerating growth, and uncovering new business opportunities, all while upholding the highest standards of user privacy. We collaborate closely with product, design, engineering, marketing, and business teams to optimize our world-class e-commerce and media streaming services.
As a Technical Product Lead focused on Data Engineering, you will be the strategic bridge between data scientists, engineers, and product teams. Your primary responsibility will be to define, design, and deliver data products that empower teams to perform cutting-edge analysis, build machine learning models, and drive impactful business outcomes. You'll combine technical product management expertise with hands-on data engineering capabilities to prototype solutions and guide implementation.
Description
In this role, you will lead the product strategy for data engineering solutions while maintaining deep technical involvement. You'll work closely with data scientists and engineers to understand their needs, prototype innovative solutions, and translate complex requirements into actionable data product roadmaps. Your unique combination of product management skills and technical depth will ensure data products are built to the highest standards of quality, scalability, and user experience.
Product Leadership Responsibilities
- Define and champion the data product vision, strategy, and roadmap for data engineering capabilities
- Develop detailed product requirements and specifications, ensuring alignment with stakeholder needs
- Manage product lifecycle from conception through delivery and iteration
- Collaborate with cross-functional teams to prioritize features and manage product backlogs
Technical Architecture & Implementation Responsibilities
- Independently design and model datasets that enable advanced analytics and ML capabilities
- Build proof-of-concepts and technical prototypes to validate product concepts
- Manage evolving data schemas ensuring extensibility while maintaining backward compatibility
- Partner with engineering teams to translate product vision into technical implementation
Stakeholder Collaboration Responsibilities
- Collaborate with Business Intelligence and Data Science teams to design solutions used across multiple workflows
- Work closely with data scientists and engineers to identify opportunities and prioritize development efforts
- Translate complex technical concepts into clear product specifications and business value propositions
Minimum Qualifications
- 7+ years of experience in Technical Product Management, Data Engineering, or Data Architecture roles
- 5+ years of hands-on data architecture design, including conceptual, logical, and physical data models
- 3+ years leading cross-functional product initiatives in data engineering or analytics domains
- 5+ years of experience in Python, SQL, and modern data stack technologies with ability to build prototypes
- Proven experience defining product strategy and roadmaps aligned with technical and business objectives
- Strong product management fundamentals including requirements gathering, prioritization, and stakeholder management
- Excellent communication, collaboration, and presentation skills with ability to influence technical and business stakeholders
- Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related field
Preferred Qualifications
- Experience with data warehouses, data lakes, real-time processing, ML platforms
- Experience working with Commerce, Subscription, or Pricing data systems
- Product management experience in data platform or analytics tools
- Track record of implementing innovative data products from concept to delivery
- Experience with data product management and customer-facing data solutions
- Master's degree in Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related field
Equal Opportunity
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.
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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 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
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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