负责 Hadoop、Spark、Hive、HBase、Presto、Flink、ClickHouse 等大数据集群的规划、部署与算力调优，保障集群 7×24 小时稳定运行。

负责集群日常运维、性能调优、容量规划、故障排查与问题根治，保障服务达成 SLA 指标。

负责大数据开源组件二次封装、功能迭代与漏洞修复，搭建通用工具与服务，赋能数据平台建设。

为数据分析团队提供底层技术支撑，协助解决平台使用过程中各类复杂技术问题。算机、软件工程、数学等相关专业，本科及以上学历，拥有 3 年及以上大数据研发相关工作经验。

具备中大型集群（PB 级数据量或 50~100 节点规模）整体规划、搭建与优化实战经验。

有 Hadoop、Spark、Hive、Presto 等开源框架源码修改、二次开发经验者优先。

精通 Hadoop、Spark、Hive、HBase、Presto、Flink、ClickHouse 等主流大数据生态组件。

熟练使用 Java、Python、Shell 进行开发，精通 HiveSQL 性能调优。

可独立完成需求分析、技术选型，能够设计高可用、高可扩展的大数据解决方案。

具备钻研精神与自驱力，沟通表达良好，拥有较强的抗压能力及集群应急处置能力。

具备 AI 开发能力，熟练使用主流 AI 编程提效工具（如 Codex、CodeCopilot 等）。

拥有大数据场景下大模型 Agent 设计、开发及项目落地经验者优先。

了解或掌握机器学习算法底层原理者优先。

## Key Responsibilities

* Design, deploy, optimize, and maintain large-scale big data clusters based on technologies such as Hadoop, Spark, Hive, HBase, Presto, Flink, and ClickHouse.

* Ensure 24×7 stability, reliability, and performance of production data platforms through proactive monitoring, capacity planning, and performance tuning.

* Troubleshoot complex system issues, conduct root cause analysis, and implement long-term solutions to meet SLA requirements.

* Develop and enhance internal platform capabilities through customization, secondary development, feature enhancements, and bug fixes of open-source big data components.

* Build reusable tools, frameworks, and platform services to improve engineering efficiency and support data platform evolution.

* Provide technical guidance and infrastructure support for data analysts, data engineers, and business teams, helping resolve complex platform-related challenges.

* Participate in architecture design, technology evaluation, and best-practice establishment for enterprise-scale data platforms.

## Qualifications

* Bachelor's degree or above in Computer Science, Software Engineering, Mathematics, or a related field.

* 3+ years of experience in big data development, platform engineering, or data infrastructure-related roles.

* Hands-on experience planning, building, and optimizing medium-to-large-scale big data clusters (50–100+ nodes or PB-scale data environments).

* Strong expertise in mainstream big data ecosystem technologies, including Hadoop, Spark, Hive, HBase, Presto, Flink, and ClickHouse.

* Proficient in Java, Python, and Shell scripting for platform development and automation.

* Advanced experience with Hive SQL optimization and large-scale query performance tuning.

* Ability to independently perform requirement analysis, technology selection, and architecture design for highly available and scalable big data solutions.

* Experience with source code modification, customization, or secondary development of open-source frameworks such as Hadoop, Spark, Hive, or Presto is highly preferred.

* Strong problem-solving skills, self-motivation, communication abilities, and the capability to handle critical production incidents under pressure.

* Familiarity with AI-assisted development tools and coding productivity platforms such as Codex, GitHub Copilot, or similar solutions.

## Preferred Qualifications

* Experience designing, developing, and deploying LLM-powered Agent solutions within big data or enterprise data platform environments.

* Understanding of machine learning algorithms and their underlying principles.

* Experience supporting AI/ML workloads on large-scale data infrastructure is a plus.