Data Platform Engineer, Emerging Technology Solutions

Summary

At Apple, new insights have a way of becoming revolutionary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.

The Emerging Technologies team specializes in building forward-looking, extremely scalable platforms. The team has a passion for solving challenging problems, exploring new domains, and engineering transformational solutions. The diversity of our team and thinking inspires innovation that runs through everything we do.

In this role, you will help build world class security solutions in the space of Anti-Phishing/Spam, Social Engineering Attack Prevention, Network/Perimeter Security and more. You will work with a passionate team with the goal of making the Internet safer for everyone. You will build full stack solutions that handle extremely large volumes of critical data harnessing the power of NoSQL, Machine Learning, Big Data, and other emerging technologies. If you're excited about being challenged, building the next generation of security solutions, and making a significant impact in the tech world, we want to hear from you.

Description

We are looking for a talented software engineer with expertise in designing and developing some of the largest and most scalable applications in the world. This core engineering role requires you to be hands-on in coding, building and tuning extremely scalable, distributed services. Our engineering team fosters creativity and builds novel solutions to deliver engineering perfection. You will work with business partners and engineering teams across Apple.

Responsibilities

• Data Engineering: Design, build, and maintain high-throughput batch and real-time data pipelines to process, aggregate, and analyze massive volumes of security telemetry across domains, IP addresses, and user entities.
• Platform Engineering: Architect, deploy, and scale robust micro-services and platform infrastructure to support high-availability, customer-facing anti-abuse services.
• End-to-End Ownership ("You Build It, You Own It"): Take full ownership of services from initial coding to production deployment, monitoring, troubleshooting, and operational maintenance within a unified team.
• Automation & Business Continuity: Invest heavily in system automation, automated testing frameworks, auto-healing systems, and resilient CI/CD pipelines to guarantee 24/7 business continuity and service uptime.
• AI-Enabled Engineering: Leverage AI-assisted coding tools and modern software engineering practices to accelerate development cycles, enhance code quality, and solve complex, cross-domain technical challenges.
• Data Store Optimization: Manage and optimize distributed NoSQL, Relational, and in-memory datastore for real-time risk scoring, pattern matching, and high-frequency aggregate state lookup.
• Observability & Telemetry: Establish comprehensive telemetry, logging, and metrics frameworks to proactively detect system bottlenecks, data quality anomalies, and production incidents.
• Cross-Functional Collaboration: Partner with cross-functional security teams, data scientists, and platform architects across Apple to deliver transformational anti-abuse solutions.

Minimum Qualifications

• Bachelor's Degree in Computer Science, Computer Engineering, or equivalent technical field.
• 2+ years of technical experience designing, building, and maintaining scalable data pipelines and platform infrastructure.
• Proficiency in Java, Python, or Scala for building data processing pipelines, distributed systems, and backend services.
• Hands-on experience operating in a "you build it, you own it" production environment with direct involvement in software deployment, observability, and operational maintenance.
• Strong understanding of distributed systems concepts, micro-services architecture, Object-Oriented Design, and RESTful service design.
• Practical experience with NoSQL datastore (e.g., Cassandra, Redis, MongoDB), as well as streaming/batch frameworks (e.g., Kafka, Spark, Flink).
• Familiarity with containerization, CI/CD automation, and cloud/platform orchestration (e.g., Docker, Kubernetes) to maintain operational business continuity.

Preferred Qualifications

• Experience developing or integrating AI/ML systems at scale, and practical familiarity with AI-assisted development tools to boost engineering productivity.
• Proven background in building customer-facing anti-abuse, anti-spam, phishing prevention, or threat detection engines.
• Versatile, multi-faceted engineering mindset capable of seamlessly bridging data engineering, platform infrastructure, and DevOps functions.
• Track record of implementing automated failover, disaster recovery, and resilience engineering for high-availability production systems.
• Strong interpersonal, written, and verbal communication skills with a passion for engineering excellence.
• M.S. or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent experience.