Sr. Data Platform Engineer, Emerging Technology Solutions

Apple

19h

About The Position

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. 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.

Requirements

• Bachelor’s Degree in Computer Science/Computer Engineering or equivalent.
• 5+ years of technical experience designing, building, and maintaining data pipelines and platforms.
• Proven track record of technical leadership in a "you build it, you own it" operational model, taking end-to-end ownership of complex production systems.
• Deep expertise in distributed systems architecture, event-driven systems, Object-Oriented Analysis and Design, and high-concurrency backend services.
• Extensive hands-on experience with Relational databases (e.g., PostgreSQL) and NoSQL data stores (e.g., Cassandra, Redis, MongoDB), as well as streaming/batch frameworks (e.g., Kafka, Spark, Flink) operating at scale.
• Strong expertise in container orchestration, infrastructure automation, and cloud/platform orchestration (e.g., Docker, Kubernetes, GitOps) to enforce 24/7 business continuity.
• Experience developing AI/ML systems at scale in production or in high-impact research environments.
• Experience with LLM training/fine-tuning.
• Hands-on experience applying common machine learning optimization techniques, like quantization and distillation, to reduce the resource consumption and/or eliminate latency.
• Dedicated and self-motivated.
• Innovative, thinks out of the box, and have a strong drive for excellence.
• Good interpersonal skills.
• Have good oral/written communication skills.

Nice To Haves

• Experience with vector stores, ranking and retrieval techniques is a plus.

Responsibilities

• Lead the architectural design and implementation of scalable, low-latency batch and real-time data pipelines to aggregate, process, and analyze massive volumes of anti-abuse telemetry across domains, IP addresses, and user entities.
• Architect, deploy, and scale highly resilient micro-services and platform infrastructure supporting mission-critical, customer-facing anti-abuse engines.
• Champion a "you build it, you own it" engineering culture by setting architectural standards and taking end-to-end accountability for system health, performance, deployment automation, and operational readiness.
• Architect robust system automation, auto-healing mechanisms, chaos testing, and CI/CD pipelines to guarantee uninterrupted business continuity and rapid disaster recovery.
• Drive the adoption of AI-assisted development tools and modern software engineering practices across the team to accelerate development velocity, elevate code quality, and solve multi-domain technical challenges.
• Design and optimize large-scale distributed NoSQL, Relational, and in-memory data architectures optimized for real-time risk evaluation, pattern matching, and high-frequency aggregate state lookup.
• Define and implement enterprise-grade observability, telemetry, and alerting strategies to proactively identify performance degradation, data quality issues, and security threats.
• Provide technical leadership and mentorship to junior and mid-level engineers, while partnering with cross-functional security researchers, data scientists, and senior leadership across Apple to drive long-term technical strategy.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior