I have extensive experience with Amazon S3, having used it to manage large datasets for various projects. My approach involves optimizing storage costs by tiering data based on access patterns and lifecycle policies. I also ensure data security through encryption and access control lists, maintaining high availability and durability standards.

Ensuring data integrity and security during cloud migration involves several steps. I use secure transfer protocols like SFTP or VPNs for initial data movement. Post-migration, I implement robust access controls, encryption at rest and in transit, and regular audits to monitor data integrity and security.

I optimize data processing by leveraging cloud-native services like AWS Lambda or Google Cloud Functions for event-driven processing. I also use managed services like AWS Glue for ETL jobs, which reduces operational overhead. Additionally, I scale resources dynamically based on workload, ensuring cost-efficiency and performance.

I have hands-on experience with Apache Spark, which I've used for large-scale data processing and machine learning tasks. My approach includes using Spark's in-memory computing capabilities to speed up data processing and integrating it with other big data tools like Kafka for real-time data streaming.

In a cloud environment, I implement disaster recovery by using multi-region deployments and automated backup solutions. I ensure data redundancy and quick recovery times by regularly testing backup and restore processes. Additionally, I use cloud-native tools for continuous data protection and compliance with industry standards.