Data Analyst

Job Description Summary

Activities contributing to the design and development of products, solutions and systems. Includes activities linked to technical improvement of existing products and components Impacts quality of own work and the work of others on the team. Executes standard operational/technical tasks typically subject to instructions and work routines. There is latitude to rearrange the sequence to complete task/duties based on changing work situations.

Job Description

We are seeking a highly motivated Data Analyst to support the Advanced Manufacturing Engineering (AME) team. The role focuses on transforming manufacturing data into actionable insights that improve process performance, yield, quality, cycle time, and operational efficiency. The analyst will work closely with Process Engineers, Yield Engineers, Production, Quality, and Operations teams to drive data-driven decision making across the manufacturing line.

Key Responsibilities

Manufacturing Data Analytics

• Analyze manufacturing, process, equipment, and quality data to identify trends, correlations, and opportunities for improvement.
• Develop and maintain dashboards, reports, and KPIs that monitor line performance, yield, scrap, throughput, and cycle time.
• Support investigations of process excursions, defects, and yield losses through data analysis and visualization.
• Perform root cause analysis using statistical methods and manufacturing datasets.
  
  

• Design and maintain Power BI dashboards and automated reporting solutions.
• Create meaningful visualizations for engineering, operations, and leadership reviews.
• Generate daily, weekly, and monthly performance reports for manufacturing management.
  
  

• Partner with Process and Yield Engineers to evaluate process capability and identify improvement opportunities.
• Support Design of Experiments (DOE) analysis and interpretation of experimental results.
• Quantify the impact of process changes through statistical analysis.
• Monitor process health indicators and establish early-warning detection systems for deviations.
  
  

• Develop and maintain SQL queries, views, and data models from MES, SPC, ERP, and manufacturing databases.
• Automate data collection, transformation, and reporting processes.
• Ensure data integrity, consistency, and accuracy across multiple manufacturing systems.
• Support digital transformation initiatives through advanced analytics and automation.
  
  

• Work closely with manufacturing, engineering, quality, and supply chain teams.
• Present analytical findings and recommendations to technical and management audiences.
• Provide training and guidance on data interpretation and dashboard utilization.
  
  

• Bachelor's degree in:
• Industrial Engineering
• Statistics
• Data Science
• Computer Science
• Engineering
• Applied Mathematics
• Related technical field
  

• 2+ years of experience in data analytics, manufacturing analytics, or business intelligence.
• Experience working in manufacturing, semiconductor, medical device, or industrial environments is preferred.
  
  

• Strong SQL skills for data extraction and analysis.
• Experience with Power BI, Tableau, or similar BI platforms.
• Proficiency in Python, R, or statistical analysis tools.
• Strong Excel and data manipulation skills.
• Knowledge of statistical analysis and process capability metrics.
  
  

• Experience with:
• MES systems
• SPC systems
• Manufacturing databases
• Semiconductor manufacturing processes
• Lean Manufacturing and Six Sigma methodologies
• Familiarity with machine learning and predictive analytics.
  

• Strong analytical and problem-solving skills.
• Ability to translate complex data into actionable business recommendations.
• Attention to detail and commitment to data accuracy.
• Excellent communication and presentation skills.
• Ability to work effectively in a fast-paced manufacturing environment.
• Strong teamwork and stakeholder management skills.
  
  

• Improve visibility of manufacturing performance through advanced dashboards and reporting.
• Accelerate root cause investigations through data-driven analysis.
• Increase adoption of data-driven decision making within AME and Operations.
• Reduce manual reporting efforts through automation.
• Support measurable improvements in yield, quality, productivity, and cycle time.
  
  

• Power BI
• SQL Server
• Python
• Excel
• Manufacturing Execution Systems (MES)
• Statistical Process Control (SPC) Systems
• Azure Data Platform (preferred)