Site Reliability Engineer, Apple Data Platform - Jobs - Careers at Apple
- Operate with a customer-centric mindset to screen, monitor, and triage production and non-production environments encompassing data processing, ML/AI, and multi-cloud infrastructure.
- Participate in a rotating on-call schedule across supported services, including occasional weekday and weekend coverage.
- Serve as a primary point of contact for internal customers seeking technical resolution — clearly communicating status, root cause, and next steps during active issues.
- Own the operational health of big data platform services as SME — driving reliability, support, and customer guidance.
- Partner with dev teams across time zones to own the customer experience for services — understanding architecture and establishing the observability benchmarks
- Build automation and self-healing tooling that reduce manual toil and scales the team's operational capacity.
- Identify, escalate, and resolve production issues to protect platform reliability and customer experience.
- Champion customer success by helping internal teams understand platform capabilities and adopt tools effectively.
- Collaborate with SRE and dev partner teams, engineering, and program management to align execution with team and org goals.
- Bachelor's Degree in Computer Science, an engineering-related field, or equivalent related experience.
- 3+ years in a Site Reliability Engineering, DevOps, or Infrastructure-focused role.
- Proficient in handling production databases and distributed-SQL engines with experience in Query Tuning and Optimizations.
- Proficient in scripting languages (Shell, Python)
- Deep understanding of one or more Big Data technologies (Spark, Flink, Airflow, Trino, Notebooks).
- Strong Experience with Kubernetes and AWS services- handling IAM (roles, policies, permission boundaries, KMS), EKS, RDS, S3 and cloud storage/networking fundamentals.
- Strong experience with implementing observability systems and practices: metrics, logging, tracing, alerting, SLOs, error budgets, and fault analysis at scale with tools like Prometheus, Grafana, Splunk, PagerDuty.
- Excellent written and verbal communication skills, with the ability to explain technical issues clearly to non-expert customers.
- Solid grounding in SRE principles, with prior on-call, production-support, or customer-facing support role experience.
- Familiarity with MCP-based tooling and ML lifecycle/dataset management systems.
- Prior experience in a customer-facing or technical support role, with a demonstrated passion for customer success.
- Working knowledge of CI/CD pipelines and deployment workflows.
- Familiarity with data pipeline orchestration and workflow scheduling patterns.
- A track record of automating manual operations through scripting or tooling.
- Intellectual curiosity and a drive to keep learning — for yourself, your team, and the org.
- Comfortable leveraging AI-assisted development tools (e.g., Claude Code) to accelerate prototyping, code generation, and documentation, and able to critically review and validate AI-generated output before it ships.
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Required Skills
Required Languages
🇬🇧 English