Manufacturing Data Analyst – Automotive
| HCL Global System
2 days ago
On-site
Georgetown, Kentucky, United States
Manufacturing Data Analyst – Automotive
location: Georgetown, KY or within 1 hour (this includes Lexington, even Cincinnati, Louisville). Able to be at the Georgetown plant regularly is the important part.
Manufacturing Data Analyst – Automotive
automotive manufacturing or a comparable discrete manufacturing environment.
manufacturing processes and shop-floor operations.
SQL
data-querying
Do you have experience in automotive manufacturing or a comparable discrete manufacturing environment?
Do you have a strong understanding of manufacturing processes and shop-floor operations?
MUST PROVIDE LINKEDIN LINK IN SUBMISSION
Manufacturing Data Analyst – Automotive
Role Overview
The Manufacturing Data Analyst applies manufacturing expertise, data analysis, and data modelling to help automotive organizations improve production performance, quality, cost, and efficiency.
Working at the intersection of manufacturing operations, manufacturing systems, data engineering, and analytics, the role is responsible for understanding manufacturing data, developing data models, integrating information from multiple systems, and transforming complex operational data into actionable insights.
The ideal candidate combines strong analytical and data-modelling capabilities with practical knowledge of automotive manufacturing environments, enabling them to understand not only what the data is showing, but also how manufacturing processes and systems should be represented within a data model.
Key Skills & Qualifications
• Experience in automotive manufacturing or a comparable discrete manufacturing environment.
• Strong understanding of manufacturing processes and shop-floor operations.
• Experience designing and developing data models for manufacturing analytics.
• Strong SQL and data-querying skills.
• Experience with relational data modelling, dimensional modelling, or semantic modelling.
• Experience working with large and complex operational datasets.
• Experience integrating data from multiple manufacturing and enterprise systems.
• Experience with MES/MOM, ERP, QMS, PLM, SCADA, historians, or equipment data platforms.
• Experience developing dashboards and analytics using Power BI, Tableau, or similar tools.
• Strong understanding of data quality, data structures, relationships, and data governance.
• Ability to translate manufacturing processes into logical data structures and analytical models.
• Strong communication skills and the ability to work with both technical and manufacturing stakeholders.
Preferred Qualifications
• Experience with Python, R, or other analytical programming languages.
• Advanced SQL and data transformation experience.
• Experience with Power BI semantic models, DAX, or similar analytical modelling technologies.
• Experience with data warehouses, data lakes, lakehouses, or modern cloud data platforms.
• Knowledge of industrial data protocols and manufacturing technologies.
• Experience with manufacturing information models or industrial data standards.
• Experience with Lean Manufacturing, Six Sigma, or continuous-improvement methodologies.
• Experience developing predictive or machine-learning models for manufacturing applications.
• Experience connecting operational KPIs to financial and business outcomes.
location: Georgetown, KY or within 1 hour (this includes Lexington, even Cincinnati, Louisville). Able to be at the Georgetown plant regularly is the important part.
Manufacturing Data Analyst – Automotive
automotive manufacturing or a comparable discrete manufacturing environment.
manufacturing processes and shop-floor operations.
SQL
data-querying
Do you have experience in automotive manufacturing or a comparable discrete manufacturing environment?
Do you have a strong understanding of manufacturing processes and shop-floor operations?
MUST PROVIDE LINKEDIN LINK IN SUBMISSION
Manufacturing Data Analyst – Automotive
Role Overview
The Manufacturing Data Analyst applies manufacturing expertise, data analysis, and data modelling to help automotive organizations improve production performance, quality, cost, and efficiency.
Working at the intersection of manufacturing operations, manufacturing systems, data engineering, and analytics, the role is responsible for understanding manufacturing data, developing data models, integrating information from multiple systems, and transforming complex operational data into actionable insights.
The ideal candidate combines strong analytical and data-modelling capabilities with practical knowledge of automotive manufacturing environments, enabling them to understand not only what the data is showing, but also how manufacturing processes and systems should be represented within a data model.
Key Skills & Qualifications
• Experience in automotive manufacturing or a comparable discrete manufacturing environment.
• Strong understanding of manufacturing processes and shop-floor operations.
• Experience designing and developing data models for manufacturing analytics.
• Strong SQL and data-querying skills.
• Experience with relational data modelling, dimensional modelling, or semantic modelling.
• Experience working with large and complex operational datasets.
• Experience integrating data from multiple manufacturing and enterprise systems.
• Experience with MES/MOM, ERP, QMS, PLM, SCADA, historians, or equipment data platforms.
• Experience developing dashboards and analytics using Power BI, Tableau, or similar tools.
• Strong understanding of data quality, data structures, relationships, and data governance.
• Ability to translate manufacturing processes into logical data structures and analytical models.
• Strong communication skills and the ability to work with both technical and manufacturing stakeholders.
Preferred Qualifications
• Experience with Python, R, or other analytical programming languages.
• Advanced SQL and data transformation experience.
• Experience with Power BI semantic models, DAX, or similar analytical modelling technologies.
• Experience with data warehouses, data lakes, lakehouses, or modern cloud data platforms.
• Knowledge of industrial data protocols and manufacturing technologies.
• Experience with manufacturing information models or industrial data standards.
• Experience with Lean Manufacturing, Six Sigma, or continuous-improvement methodologies.
• Experience developing predictive or machine-learning models for manufacturing applications.
• Experience connecting operational KPIs to financial and business outcomes.