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Benefits & Perks
•Healthcare
•401(k)
•Equity
•Healthcare
•401k
•Equity
Required Skills
Graph query languages
Database engineering
Graph databases
The people here at Apple don't just build products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that encourages the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
Come join the team that builds the data assets for Apple's products and services. AiDP - Data Services within Apple designs, deploys, and maintains the systems that store and manage business-critical data. We ensure databases are secure, highly available, and optimized for performance. Our team supports application, analytics, and AI workloads by providing reliable data access as well as lifecycle management, backups, disaster recovery, security, and compliance.
We are looking for passionate and dedicated Graph database professionals to join our AiDP - Data Services Engineering team.
Description:
Our AiDP - Data Services team invites passionate Graph Database Engineers to join us in shaping the future of graph technologies that power some of Apple's most important services. Our engineers design, build, and operate large-scale graph database systems that enable deep insights into highly connected data across different domains. You will be joining a team of experts working on modern graph database platforms, distributed systems, and storage engineering, pushing the boundaries of performance, scalability, and availability for graph workloads at Apple. Your work will help unlock new capabilities deployed at massive scale across our global data centers and public clouds, impacting the experiences of millions of Apple users every day.
Preferred Qualifications:
Proficiency in at least one programming language (Python, Java, or JavaScript) for data integration and application development
Experience with graph database platforms such as Neo4j, Amazon Neptune, Tiger Graph, Janus Graph, or ArangoDB
Solid understanding of data modeling concepts, graph theory basics, and relationship-driven architectures
Familiarity with ETL processes, API integrations, or data ingestion frameworks
Knowledge of cloud services (AWS, Azure, GCP) and managed graph database offerings
Understanding of RDF, SPARQL, or semantic web technologies
Exposure to big data ecosystems (Spark, Kafka) for graph data processing
Experience with version control systems (Git) and CI/CD workflows
Minimum Qualifications:
Bachelor's degree in Computer Science, Information Systems, or related field or equivalent practical experience
2+ years of hands-on database engineering experience, with at least 2 years working directly with graph databases
Strong proficiency in at least one graph query language: such as Cypher, Gremlin, GSQL
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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