Cloud Engineer, Health Software

Apple

About The Position

The Apple Health team is looking for a hardworking Sr. Cloud Engineer with a background in large scale engineering support. You will enjoy using technology to automate solutions and optimize outcomes focusing on data/backend engineering, continuous integration and continuous deployment in a fast-changing world of software delivery. Apple's Health team is seeking a high-energy Site Reliability Engineer. As a member of our dynamic group, you’ll have the rare and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple’s customers every day. Comfortable with weekly on-call rotation.

Requirements

Hands-on experience in engineering, Cloud, or as a software engineering staff member
Strong programming and scripting fundamentals, Python and Bash
Modern web services architectures, cloud platforms such as AWS, GCP
Source control management such as Git, SVN
Linux fundamentals, experience with hardening operating system images
Hands-on experience with Log mining frameworks like Splunk, Elastic, Prometheus, Loki etc
Container services(Docker/Kubernetes), UNIX system administration
Grafana or similar for investigating or monitoring problems on systems
Release and management of NoSQL, Zookeeper, Spark, Mesos
In-depth knowledge of build/release systems and process
BS Computer Science or equivalent experience
Passionate about Continuous Build, Integration, Test, and Delivery systems
Able to quickly learn new and existing technologies
Strong attention to detail and excellent analytical capabilities
A desire to write tools and applications to automate work rather than do everything by hand
Self-motivated, pro-active and solution-oriented individual

Responsibilities

Design, build, and maintain scalable cloud infrastructure on AWS and/or GCP to support Apple Health software services
Develop and maintain CI/CD pipelines to enable fast, reliable, and repeatable software delivery
Write automation tools and scripts in Python and Bash to reduce manual toil and improve operational efficiency
Monitor system health and performance using observability tools such as Grafana, Prometheus, Splunk, and Loki, and drive resolution of incidents
Manage and optimize containerized workloads using Docker and Kubernetes in large-scale production environments
Administer and support distributed data systems including NoSQL databases, Zookeeper, Spark, and Mesos
Collaborate cross-functionally with software engineers, security teams, and product teams to define and implement infrastructure best practices
Own and improve build and release systems, ensuring high availability, reliability, and performance at scale
Conduct root cause analysis on production incidents and implement preventative measures to reduce recurrence
Participate in capacity planning, performance tuning, and cost optimization across cloud environments
Maintain source control workflows and repository hygiene using Git or SVN
Document systems, runbooks, and operational procedures to support team knowledge sharing and continuity