Senior Backend Software Engineer, Data Science & Analytics Platform Engineering
Apple
Software Engineering, Data Science
Austin, TX, USA
Posted on Apr 17, 2026
Are you ready to make a significant impact on how one of the world's largest analytics organizations moves, serves, and governs its data? If you are passionate about building high-performance, reliable platform services at internet scale, we would love for you to apply! The Apple Services Data Science & Analytics organization drives decisions that improve the customer experience, accelerate growth, and uncover new business opportunities while respecting user privacy and adhering to regulatory policy. We work on some of the largest e-commerce and media streaming businesses in the world and have an incredible team collaborating on the best ways to improve these services for our customers! Our culture is built on rapid iteration, open debate, and independent thinking — we take calculated risks and work as analytical advisors across product, design, engineering, marketing, editorial, legal, and business teams.
As a Senior Software Engineer on the Services Data Science & Analytics Platform Engineering team, you will design, build, and operate the backend services that form the foundation of DS&A's data platform. This is high-stakes infrastructure work: every downstream consumer in DS&A and Services broadly depends on what you build. A great fit for this role is someone who thinks deeply about distributed systems, obsesses over reliability and performance, and takes pride in building platform primitives that other engineers love to build on.
- You will own core platform services end-to-end — from API design and query routing through caching infrastructure and data lineage — ensuring they perform reliably at the scale and latency demands of one of the world's largest analytics organizations.
- You'll collaborate closely with Data Engineering, Data Science, Machine Learning Engineering, Insight Engineering, and Core Engineering teams, making architectural decisions that directly shape the scalability and durability of DS&A's analytical foundation.
- Over time, you'll influence platform strategy, mentor engineers across the team, and help drive the technical roadmap for how DS&A manages, governs, and serves its data at scale.
- 8+ years of experience building and operating high-performance, production-grade backend API services
- Expert proficiency in Python or Node.js/TypeScript — including async programming, type safety, and framework-level development (FastAPI, Express, or equivalent)
- Demonstrated experience designing and operating distributed systems with strict reliability and latency SLAs
- Strong proficiency with API design and service-to-service communication patterns (REST, gRPC, GraphQL, or equivalent)
- Hands-on experience with multi-layer caching architectures (in-process, Redis, or similar) and cache invalidation strategies
- Extensive experience building systems that integrate with distributed and high-performance data stores — Snowflake, Trino, Spark, PostgreSQL, or equivalent
- Proficiency with Kubernetes, deployment, HPA, StatefulSets, namespace management
- Strong observability practice, Prometheus, Grafana, OpenTelemetry, or equivalent
- BS in Computer Science, Engineering, or related field, or equivalent professional experience
- Experience building data catalog, metadata, or lineage systems
- Familiarity with Apache Iceberg or other open table formats
- Experience with CI/CD pipeline design and enforcement gates in large engineering organizations
- Familiarity with AI/ML infrastructure or experience integrating LLM-powered capabilities into platform services
- MS in Computer Science, Engineering, or related field
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.