薪资绩效经理
岗位信息
| 招聘单位 | 天孚通信 |
|---|---|
| 工作地点 | 高安市 |
| 官方更新时间 | 2026-08-14T16:47:13.3661735 |
职位描述
岗位内容:
1、 根据公司发展战略规划目标,负责建立、修订和完善薪资绩效管理体系、制度;
2、负责公司薪资核算工作,建立复核机制并持续优化完善;
3、负责分析公司人工成本产值及薪资体系的激励效果,提出薪资政策调整建议;
4、负责计件工资标准化,主导计件工资分析优化,推进计件工资核算系统化;
5、负责组织公司开展外部薪酬水平调研,保持薪酬对外竞争力;
6、负责组织开展绩效指标分解和修订工作,制定年度和季度绩效考核计划;
7、负责收集绩效数据,开展绩效考评,并对绩效考核进行分析汇总、审查;
8、负责组织各部门开展绩效沟通工作,持续优化绩效考核逻辑、制度落地。
1. In accordance with the company's strategic development planning goals, be responsible for establishing, revising and improving the salary and performance management system and regulations;
2. Be responsible for the company's salary calculation work, establish a review mechanism and continuously optimize and improve it;
3. Be responsible for analyzing the incentive effect of the company's labor cost output value and salary system, and put forward suggestions for adjusting salary policies;
4. Be responsible for the standardization of piece-rate wages, lead the analysis and optimization of piece-rate wages, and promote the systematization of piece-rate wage accounting;
5. Be responsible for organizing the company to conduct external salary level research and maintain the competitiveness of salaries externally;
6. Be responsible for organizing and carrying out the decomposition and revision of performance indicators, and formulating annual and quarterly performance assessment plans;
7. Be responsible for collecting performance data, conducting performance evaluations, and analyzing, summarizing and reviewing the performance appraisals;
8. Be responsible for organizing all departments to carry out performance communication work, continuously optimizing the logic of performance assessment and the implementation of the system.
任职要求
1、本科及以上学历;
2、5年以上制造业薪资绩效模块经验;
3、具有现代人力资源管理、劳动法律法规、合同法等方面培训经验;
4、较强的数据分析能力,良好的沟通能力和协调能力。
1. Bachelor degree or above;
2. 5+ years of experience in large-scale manufacturing in Salary and Performance module;
3. Have training experience in modern human resource management, labor laws and regulations, contract law, etc;
4. Strong data analysis skills, good communication and coordination abilities.
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