Data Analyst Supplier Quality Engineering (Integrated Supply Chain)
Location: Remote (Travel as in when required)
VISA: USC and GC
Must Have :
- SQL Database, Data analytics including Data ETL preferably with Alteryx tool
- Data reporting and visualization with Tableau and/or Power BI.
- Supplier Quality Engineering (SQE)
- SQL Database
- Dashboard, Visualization and Reporting, with Tableau and/or PowerBI
- Data Extraction, Data Transformation and Data Loading with Alteryx or comparable ETL
- Experience : Any Manufacturing
- Aerospace domain preferred
- Relevant Experience : around 10 Years
- Workflow Automation
Organization
Supplier Quality Engineering (SQE)
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