Sr Cloud Infrastructure Engineer - Data

Job Description:

Pacific Life is investing in bright, agile, and diverse talent to contribute to our mission of innovating our business and creating superior customer experience. We are actively seeking a talented Senior Cloud Infrastructure Engineer - Data to join our Enterprise data team in Newport Beach, CA. This role can be on-site, hybrid or 100% remote. 

The Senior Cloud Infrastructure Engineer for Data is responsible for designing, implementing, and optimizing the cloud infrastructure that supports the organization’s data, analytics, and AI platforms. This role will ensure the seamless integration and scaling of cloud services to meet the demands of data-driven applications, analytics pipelines, and AI/ML workloads. The Senior Infrastructure Engineer will collaborate with data teams, DevOps, and AI specialists to build robust, secure, and high-performance environments that enable advanced data processing and machine learning capabilities.

As a Senior Cloud Infrastructure Engineer – Data, you will be responsible for designing, deploying, and optimizing cloud infrastructure to support the organization’s data, analytics, and AI platforms. You will play a key role in building scalable and secure environments that enable advanced data processing and analytics operations. You will collaborate with data architects and data engineers to build robust, secure, and high-performance environments while ensuring and cost efficiency and reliability aligning with evolving business needs.

How will you make an impact:

• Cloud Infrastructure Design and Implementation: Design, deploy, and manage scalable, high-performance cloud infrastructure for data and analytics platforms using AWS.
• Support for Data Platforms: Ensure the cloud infrastructure supports large-scale data pipelines, analytics workloads, and real-time data processing for platforms like Snowflake, Matillion, dbt and other data lakes and warehouses.
• AI/ML Platform Integration: Design and manage cloud environments for AI/ML models, including platforms such as Amazon SageMaker, Azure Machine Learning, or Google AI Platform, ensuring optimal compute, storage, and networking configurations.
• Performance and Cost Optimization: Continuously optimize cloud resources for performance and cost efficiency. Implement autoscaling, monitoring, and tuning strategies to balance compute power and operational costs for data processing and AI workloads.
• Automation and Infrastructure-as-Code: Develop and maintain Infrastructure-as-Code (IaC) solutions using tools like Terraform and CloudFormation, to automate cloud infrastructure provisioning, configuration, and management.
• Security and Compliance: Implement best practices for cloud security, including data encryption, identity and access management (IAM), and network security according to enterprise information security standards. Ensure infrastructure complies with relevant industry regulations (e.g., GDPR, HIPAA) and internal data governance policies.
• Monitoring and Incident Management: Set …