供应商质量工程师
Supplier Quality Engineer
职位职责
集成供应链组织正在寻找一名专业的数据分析师，以支持供应商质量工程（SQE）职能。该职位将专注于供应商质量数字化、分析和可视化，使SQE管理层和相关方能够进行数据驱动的决策。
数据分析师将与供应商质量工程团队及现有的数字化团队紧密合作，了解现有工作流程，自动化数据管道，并提供交互式仪表板和临时分析结果，以提高供应商质量表现、风险可见性和运营效率。
主要职责
1. 仪表板与分析开发
- 构建并维护提供清晰、可操作的供应商质量表现、风险、趋势和纠正措施有效性的可视化仪表板。
- 将复杂、多源的数据集转化为直观、可决策的可视化结果，供SQE管理层和相关方使用。
2. 数字化与流程对齐
- 与当前的SQE数字化团队密切合作，了解现有的数据流、报告流程和分析需求。
- 确保新的分析解决方案与已有的SQE流程、标准和治理模型保持一致。
3. 数据管道与自动化
- 使用Alteryx（或等效ETL工具）开发、维护并自动化供应商质量工程的数据管道和工作流程。
- 确保SQE分析的数据准确性、可重复性、可扩展性和及时更新。
- 记录数据流、转换过程和关键绩效指标（KPI）定义，以支持标准化和持续性。
4. 交互式可视化与报告
- 使用Tableau、Power BI、基于React的仪表板或等效工具设计、构建和维护交互式仪表板。
- 创建支持供应商质量决策的分析，包括绩效监控、风险识别和持续改进计划。
- 优化仪表板的可用性、性能和相关方的采用率。
5. 临时分析与高管支持
- 进行临时数据分析，以支持SQE项目、管理层请求和供应商评审。
- 以清晰、简洁且以业务为导向的方式向SQE相关方和管理层展示发现、趋势和见解。
- 提供数据支持的洞察，以支持治理审查、运营审查和持续改进讨论。
所需资格与经验
- 数据科学、统计学或相关领域的学士学位
查看英文原文
Role Purpose
Integrated Supply Chain organization is seeking a dedicated Data Analyst to support the Supplier Quality Engineering (SQE) function. This role will focus on supplier quality digitization, analytics, and visualization, enabling data‑driven decision‑making across SQE leadership and stakeholders.
The Data Analyst will work closely with the Supplier Quality Engineering organization and existing digitization teams to understand current workflows, automate data pipelines, and deliver interactive dashboards and ad‑hoc insights that improve supplier quality performance, risk visibility, and operational effectiveness.
Key Responsibilities
1. Dashboard & Analytics Development
- Build and maintain visual dashboards that provide clear, actionable insights into supplier quality performance, risks, trends, and corrective action effectiveness.
- Translate complex, multi‑source datasets into intuitive, decision‑ready visualizations for SQE leadership and stakeholders.
2. Digitization & Workflow Alignment
- Work closely with the current SQE digitization team to understand existing data flows, reporting workflows, and analytics requirements.
- Align new analytics solutions with established SQE processes, standards, and governance models.
3. Data Pipelines & Automation
- Develop, maintain, and automate data pipelines and workflows for Supplier Quality Engineering using Alteryx (or equivalent ETL tools).
- Ensure data accuracy, repeatability, scalability, and timely refresh of SQE analytics.
- Document data flows, transformations, and KPI definitions to support standardization and continuity.
4. Interactive Visualization & Reporting
- Design, build, and maintain interactive dashboards using Tableau, Power BI, React‑based dashboards, or equivalent tools.
- Create analytics that support supplier quality decision‑making, including performance monitoring, risk identification, and continuous improvement initiatives.
- Optimize dashboards for usability, performance, and stakeholder adoption.
5. Ad‑hoc Analysis & Executive Support
- Perform ad‑hoc data analysis to support SQE initiatives, leadership requests, and supplier reviews.
- Present findings, trends, and insights to SQE stakeholders and leadership in a clear, concise, and business‑focused manner.
- Support governance reviews, operational reviews, and continuous improvement discussions with data‑backed insights.
Required Qualifications & Experience
- Bachelor’s degree in Data Science, Statistics, Engineering, or a related field.
- Hands‑on experience with Alteryx or comparable ETL/data preparation tools for workflow automation and analytics enablement.
- Experience with data visualization tools such as Tableau and/or Power BI (experience with React‑based dashboards is a plus).
- Strong proficiency in SQL for data extraction, transformation, and analysis.
- Experience working with large, complex datasets from multiple systems.
- Strong problem‑solving, communication, and stakeholder management skills, with the ability to translate data into meaningful business insights.
Preferred Experience (Nice to Have)
- Experience supporting Supplier Quality, Manufacturing Quality, or Supply Chain organizations.
- Familiarity with quality metrics, corrective actions, audits, and supplier performance management.
- Experience in aerospace, industrial, or regulated manufacturing environments.
- Exposure to ERP and quality management systems
Originally posted on Himalayas