Data Engineer – Manufacturing Quality & Automation (Onsite - Greenville, NC)

OMG Technology•Raleigh, NC

1d•Onsite

About The Position

We are looking to hire a candidate with the mentioned skill sets and experience for one of our clients within the pharmaceutical Industry. This is a 6+ months contracting role, with potential for extension. We are seeking a highly motivated Data Engineer with expertise in Manufacturing Quality Assurance (QA), Process Automation, and Business Intelligence. The ideal candidate will be responsible for designing and implementing scalable data solutions, automating business and quality processes using UiPath or Microsoft Power Automate, and developing actionable insights through Power BI dashboards and reports. This role will work closely with Manufacturing Operations, Quality Engineering, Business Analysts, and IT teams to improve product quality, operational efficiency, and data-driven decision-making.

Requirements

5+ years of experience in Data Engineering, Manufacturing Analytics, Quality Systems, or Automation.
Hands-on experience working in a Manufacturing / Production environment.
Strong understanding of Manufacturing Quality / QA processes, including CAPA and process validation.
Expertise in SQL and relational databases.
Experience with ETL/ELT tools and data integration frameworks.
Hands-on experience with Power BI, DAX, Power Query, and data visualization.
Experience with UiPath and/or Microsoft Power Automate.
Knowledge of Supply Chain processes.
Experience working with ERP systems such as SAP, Oracle, or similar platforms.
Programming experience in Python, PySpark, or similar technologies.
Experience with data validation, data quality, governance, and testing.
Must be able to work 5 days onsite in Greenville, NC.

Responsibilities

Design, build, and maintain scalable data pipelines and ETL/ELT processes.
Integrate data from manufacturing systems, MES, ERP, quality systems, IoT devices, and enterprise applications.
Develop and maintain data models, data warehouses, and lakehouse architectures.
Ensure data quality, accuracy, governance, and security across all data assets.
Optimize data processing workflows for performance and reliability.
Analyze manufacturing and quality data to identify trends, defects, and process improvement opportunities.
Support quality initiatives through data validation, root cause analysis, and KPI tracking.
Develop manufacturing quality metrics and reporting frameworks.
Collaborate with QA teams to establish automated monitoring and data quality checks.
Design and develop RPA solutions using UiPath or Microsoft Power Automate.
Automate manual business and quality processes to improve productivity and reduce errors.
Integrate automation workflows with ERP, quality systems, SharePoint, Teams, and other enterprise applications.
Monitor and enhance automation performance and reliability.
Develop interactive dashboards, scorecards, and reports using Power BI.
Create semantic models, DAX calculations, KPIs, and drill-down analytics.
Enable self-service reporting and business insights for manufacturing and quality stakeholders.
Optimize report performance and governance.