The Quality Operations Engineering Analyst provides analytical support to the Elkton Quality departments through data-driven insights and process improvement initiatives. This role involves collecting, analyzing, and visualizing Quality-related data to enhance compliance, efficiency, and decision-making. The Analyst will also assist with reporting, issue identification, and continuous improvement initiatives within Quality Operations.

Key Responsibilities

• Partner with Elkton Quality teams to identify and fulfill their data analysis and reporting needs.
• Ensure the effectiveness of the nonconformance (NC) process by preparing timely Quality metrics, performing data analysis, and presenting findings in a clear, actionable manner.
• Design and maintain dashboards and visualizations (e.g., NC and Quality metrics) in collaboration with developers to communicate trends and performance indicators across the organization.
• Automate manual data collection and analysis workflows to improve accuracy and efficiency.
• Identify untapped Quality data sources and apply appropriate statistical or analytical methods.
• Use mathematical and statistical techniques to collect, trend, and interpret Quality data.
• Recommend, implement, and track continuous improvement initiatives within Quality Operations.
• Support administrative and cross-functional Quality activities as needed.
• Adhere to all Environmental Health & Safety (EHS) and Quality System standards to ensure compliance and promote a safe, sustainable workplace.
• Represent the Quality Engineering team in performance meetings, contributing ideas to drive organizational improvement.

Qualifications

Knowledge, Skills, and Abilities

• Strong analytical skills with the ability to aggregate and interpret data from multiple sources.
• Proficiency in data visualization and clear graphical presentation of insights.
• Excellent verbal and written communication skills; strong organizational ability.
• Demonstrated critical thinking and problem-solving capability, including identifying root causes and recommending effective corrective actions.
• Quality-oriented mindset: process-driven, detail-focused, customer-centered, and results-oriented.
• Working knowledge of statistical charts and methodologies.

Education and Experience

• Bachelor’s degree in Engineering, Science, Data Science, Mathematics, or a related discipline required (or equivalent combination of education and experience).
• Minimum of 3 years of experience in engineering, quality assurance, or manufacturing support.
• Experience in FDA-regulated industries preferred.
• Proficiency in data analysis and automation tools such as Power BI, Minitab, Python, SAS, or VBA preferred.
• Familiarity with SAP reporting and Data Lake environments a plus.
• Lean/Six Sigma or ASQ-CQE certification preferred.