Senior Software Data Engineer

Apple

United States

United States

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À propos

People at Apple don't just build products - they craft the kind of experience that has revolutionized entire industries. The diverse collection of our people and their ideas inspire innovation in everything we do. Imagine what you could do here! Join Apple, and help us leave the world better than we found it.\\nThe Analytics Platforms & Experiences (APX) team is at the forefront of revolutionising Data Engineering. We drive significant increases in efficiency and productivity through a flawless ecosystem of frameworks and products that unlock observability, knowledge and enable data quality-driven orchestration at scale. APX is part of the broader Apple Services Engineering division that powers App Store, Apple TV+, Apple Music, Apple Podcasts, Apple Books, Fitness+, the iTunes Store and more.\\nThe APX Bedrock team is the foundational platform layer within APX, responsible for building the systems and services that underpin data engineering excellence across the organization. We are seeking a Senior Software Data Engineer who brings deep technical expertise and the strategic thinking to shape the future of our data engineering platform. In this role, you will influence the broader technical vision, drive platform-wide architectural decisions, and establish patterns that raise the engineering bar across the organization. You will bridge hands-on engineering excellence with forward-looking platform thinking, working alongside architects and cross-functional teams to transform how data engineers work at Apple.
As a Senior Software Data Engineer on the APX Bedrock team, you will be a highly impactful technical contributor who combines deep engineering craftsmanship with platform-wide thinking. You will own critical platform components end-to-end while actively shaping the technical direction of the team and influencing the broader organization.\n\n* Lead design and implementation of core platform services supporting data application authoring, metadata management, dataset lifecycle tracking, and orchestration at scale\n* Architect and build high-performance Java-based backend services and APIs that form the backbone of the data engineering platform\n* Own data modeling and database design decisions, establishing best practices for schema design, indexing strategies, and query optimization across relational and non-relational data stores\n* Design and operate scalable data processing pipelines using Apache Spark, Apache Flink, and modern orchestration frameworks\n* Proactively identify architectural gaps and drive initiatives that improve platform scalability, reliability, and developer experience\n* Define engineering standards and patterns adopted across the broader team and organization\n* Evaluate emerging technologies and contribute to strategic decisions that shape the platform roadmap\n* Mentor engineers across experience levels and drive a culture of technical excellence\n* Leverage AI-powered development tools and help define how AI-augmented workflows are adopted and scaled within the team
Bachelor's or Master's Degree in Computer Science, Engineering, or equivalent professional experience\n8+ years of software engineering experience with significant focus on data platform or large-scale distributed systems\nExpert-level Java programming with a strong track record of architecting and delivering complex, production-grade backend services\nDeep experience with relational databases including advanced data modeling, schema design, and query optimization at scale\nExpert-level experience with Apache Spark and Apache Flink, and distributed data technologies including Hadoop, HDFS, and Kafka\nExtensive experience designing and operating workflow orchestration systems such as Apache Airflow at enterprise scale\nProven ability to drive end-to-end technical ownership of complex platform initiatives and influence technical direction beyond immediate team scope
Experience with non-relational or NoSQL databases and strong intuition for applying the right data storage paradigms\nProficiency in Scala, Go, or Python as complementary programming languages\nDeep experience with container orchestration tools such as Kubernetes and cloud-native infrastructure patterns\nHands-on experience with AI-powered development tools (e.g., Claude Code, Copilot) and building AI-augmented engineering workflows\nExperience architecting data quality monitoring, metadata management, or dataset lifecycle management systems at scale\nStrong background in streaming, real-time data processing, and event-driven architectures\nTrack record of mentoring senior engineers and driving technical excellence across teams\nStrong communication skills with the ability to present complex technical strategies to senior leadership

United States

Compétences linguistiques

English

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