Data Transformation and Management Specialist

The Data Transformation and Management Specialist is responsible for designing, developing, and maintaining scalable data solutions that enable efficient data integration, transformation, and analytics across the organization. This role combines data engineering expertise with supply chain analytics to support business decision-making, improve operational performance, and drive continuous improvement initiatives. The specialist ensures the integrity, availability, and quality of enterprise data while collaborating with cross-functional teams to deliver reliable data pipelines, reporting solutions, and cloud-based data platforms.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines to acquire, transform, and load data from multiple enterprise systems using batch and real-time processing methods.
• Build, optimize, and maintain ETL processes to ensure reliable, automated, and efficient movement of data across systems.
• Develop and maintain database solutions, ensuring optimal performance, scalability, and data availability.
• Clean, validate, transform, and enrich raw data to improve quality, consistency, and usability for reporting and analytics.
• Monitor data pipelines, databases, and cloud infrastructure to identify and resolve performance issues, data quality concerns, and system bottlenecks.
• Utilize cloud technologies, particularly Microsoft Azure services, to manage data storage, processing, and integration.
• Provide analytical support for supply chain and business functions through data modeling, reporting, and KPI analysis.
• Analyze supply chain performance metrics to identify trends, root causes, improvement opportunities, and actionable recommendations.
• Support inventory optimization, material planning, and planning parameter refinement through data-driven insights.
• Participate in continuous improvement initiatives, including Six Sigma and supply chain optimization projects.
• Ensure data integrity, governance, and compliance across reporting, analytics, and enterprise data solutions.
• Collaborate with data scientists, software engineers, business analysts, and functional stakeholders to understand data requirements and deliver business solutions.
• Develop and maintain documentation for data architecture, ETL processes, data models, and system configurations.
• Support the development of repeatable analytics and reporting solutions using enterprise business systems and Business Intelligence tools.