Apple-posted 4 months ago
Full-time • Mid Level
TX
5,001-10,000 employees

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.

  • Design, build, and operate large-scale graph database systems.
  • Enable deep insights into highly connected data across different domains.
  • Work on modern graph database platforms, distributed systems, and storage engineering.
  • Push the boundaries of performance, scalability, and availability for graph workloads at Apple.
  • Unlock new capabilities deployed at massive scale across global data centers and public clouds.
  • 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.
  • 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, TigerGraph, JanusGraph, 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.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service