Site Reliability Engineer - Infrastructure

Description

The team is responsible for infrastructure systems, including Storage/Computing/DB. We aim to be the leading SRE team across the industry. In the SRE team, you will have the opportunity to manage the complex challenges of scale, while using expertise in coding, algorithms, complexity analysis, and large-scale system design. We embrace a culture of diversity, intellectual curiosity, openness, and problem-solving. We also encourage ownership, self-governance and independence to work on various projects, and an environment that provides the support and mentorship needed to learn and grow as an engineer.

Responsibilities
- Reliability: Ensuring the reliability and efficiency of our core infrastructure, focusing on system capacity and stability; setting up reliability standards and recovery SOP.
- Troubleshooting and locating technical issues, bottleneck analysis, managing system high availability architecture transformation and upgrading.
- Efficiency: Building automated operation solutions for large-scale systems; partnering with system development teams for system iteration.
- Efficiency: Designing and implementing software platforms and monitoring frameworks for efficient, automated, and intelligent service-oriented architecture (SOA) governance.
- Cost: There are millions of CPUs. We should build delivery standards, and monitor and budget systems to optimize the cost of the company.
- Compliance: Designing and setting up new IDC; designing and implementing a data protection plan to meet the standard requirement.

Requirements

Minimum Qualification(s):
- Solid basic knowledge of computer software
- Understanding of Linux operating system, storage, network IO and related principles
- Familiarity with one or more programming languages, such as Python, Go, and Java
- Knowledge of design patterns and coding principles

Preferred Qualification(s):
- Bachelor's / Master's Degree in Computer Science or related major
- At least 3 years of relevant experience
- Experience with storage systems and technologies such as KV, Table, Graph, Redis, MySQL, MongoDB, MQ, and Kafka
- Experience with computing & big data systems and technologies such as Kubernetes, Docker/Containers, AIops, Spark, Flink, Function as a service, RPC Framework, and Service Mesh

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