111 applicants

Company

Crunchyroll · 13 hours ago

Staff Site Reliability Engineer - Data Engineering, Platform

San Francisco, CA

Full-time

Remote

Lead/Staff

$191K/yr - $239K/yr

12+ years exp

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Responsibilities

Maintain and enhance the reliability of our data infrastructure.

Collaborate closely with data engineers and software engineers to develop and drive 100% automation.

Implement best practices for deep monitoring and alerting.

Standardize and implement monitoring and alerting across all datastores to track key metrics like errors, latency, and throughput.

Lead efforts to keep databases up-to-date.

Implement Infrastructure as Code (IaC) for high availability and performance.

Automate key processes to enhance operational efficiency.

Define and document operational requirements.

Develop incident response processes.

Automate monitoring and compliance checks to maintain a secure and reliable data environment.

Continuously improve load testing and optimize data governance practices.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

AWS cloud platformMonitoring toolsAutomation frameworksDatabase systemsProgramming languagesCI/CD pipelinesData governanceSite reliability engineeringDatabase operationsData platformsData storesData operationsPerformance metricsDatabase internalsLifecycle management

Required

Bachelor's degree in Computer Science, Information Technology, or a related field.

12+ years of experience in site reliability engineering, database operations, or a related role with a focus on data platforms, data stores, data operations.

Extensive experience with AWS cloud platform and their data-related services.

Proficiency in monitoring tools (e.g., Datadog, CloudWatch, DevOps Guru, DB Performance Insights).

Proficiency in one or more programming languages (e.g. Python, Java).

Proficiency in automation frameworks (e.g., Terraform, Cloud Formation).

Strong understanding of various performance metrics both at a high level and at a low level like Disk/IO saturation.

Experience in identifying and eliminating the bottlenecks in the system.

Strong understanding of database internals like types of indexes, schemas, query plans.

Strong understanding of database systems (e.g., SQL, NoSQL) and experience in managing large-scale data infrastructures.

Strong understanding and hands-on implementation of CI/CD pipelines and DataOps practices.

Experience with data governance, compliance, and lifecycle management.

Ability to own and execute projects while effectively collaborating with the team to influence and shape the vision of the data engineering organization.