Full Job Description
APPLE INC has the following available in Austin, Texas. Building and operating the global database platform that powers Apple services, delivering high-performance, reliable, and scalable solutions to customers worldwide and enabling a consistent Apple experience at a global scale. Deploying and managing databases on cloud platforms (AWS and GCP) using services such as RDS, EC2, S3, EKS, and GKE to ensure cost-effective scalability and high reliability. Developing partitioning and sharding strategies across several database technologies to efficiently handle large-scale data sets while maintaining optimal read/write performance. Implementing monitoring and alerting solutions using Prometheus and Grafana to proactively detect and resolve database outages, significantly improving system uptime. Performing routine database maintenance activities, including upgrades, patch management, user access control, and automated backup implementations. Collaborating with application teams during ramp-up periods to support load testing and ensure database systems meet performance and scalability requirements. Identifying opportunities for automation of repetitive and manual database operations, and develop robust automated workflows to improve efficiency and consistency. Enforcing best practices and daily health checks for both host servers and database environments to maintain system integrity and performance. Troubleshooting and resolving complex technical issues under high-pressure scenarios, delivering scalable solutions while supporting multiple internal and external customer groups. Ensuring database security and compliance by implementing encryption, access controls, auditing, and adhering to industry standards and regulatory requirements. 40 hours/week.
Bachelor's degree or foreign equivalent in Management Information Systems or related field and 7 years of progressive, post-baccalaureate experience in the job offered or related occupation.
7 years of experience with each of the following skills is required:
Designing and maintaining distributed database systems, leveraging sharding and replication to ensure horizontal scalability and fault tolerance across multi-region deployments.
Deploying and managing database clusters on cloud platforms like AWS and GCP, utilizing services such as AWS EC2, EKS, S3, or GCP GKE for scalable, resilient database infrastructure.
Architecting infrastructure to support MongoDB workloads with high availability and performance.
Designing optimized schemas by leveraging flexible BSON data types, embedding versus referencing strategies, and comprehensive index configurations-including compound, multikey, and TTL indexes-to ensure efficient query performance, data integrity, and scalable storage.
Analyzing and tuning database queries, indexes, and server parameters using tools like mtools, Compass, and Ops Manager to improve throughput and reduce latency; monitoring performance and resource utilization via CloudWatch and Grafana; implementing caching strategies and workload balancing for optimized database efficiency.
Disaster recovery - RTO/RPO planning, Implementing backup, snapshot, and failover strategies using MongoDB Ops Manager or cloud-native tools to ensure minimal downtime and data loss in disaster scenarios.
Monitoring & Observability - Implementing end-to-end observability for database systems using tools like CloudWatch, Grafana, and Datadog; defining custom metrics, alerts, and dashboards to proactively identify bottlenecks, capacity issues, and anomalies.
Storage & I/O Management - Managing disk layouts, filesystem tuning, RAID configurations, IOPS provisioning, and storage tiering to ensure optimal read/write performance and predictable latency under varying workloads.
Database Migration - Planning and executing database migrations across versions, clusters, and cloud providers with minimal downtime, ensuring data consistency and integrity. Utilizing tools like mongomirror, mongodump or mongorestore, mongoexport or mongoimport, Ops Manager, and live migrations. Handling schema transformations, reindexing, and replica set reconfiguration, with pre- and post-migration validation and rollback strategies in place.
Using python, bash scripting to automate daily activities such as database patching, database upgrades, configuration changes, and OS patching.
Incident Response & Troubleshooting - Quickly diagnosing and resolving database issues under pressure by analyzing slow query logs, profiler outputs, diagnostic logs, and server events to identify root causes such as lock contention, replication delays, memory pressure, or storage bottlenecks, and implementing scalable solutions in coordination with cross-functional teams.
N/A
