Data Engineer

Data Integrity, Governance & SteWARDSHIP

• Establish and enforce data governance standards across ERP, data warehouse, and connected systems
• Ensure accuracy, consistency, and reliability of core datasets (item master, lead times, safety stock, supplier and customer data)
• Identify and remediate data quality issues through structured audits and data initiatives
• Define ownership, workflows, and controls for maintaining high-quality master data
• Implement monitoring systems to proactively detect and resolve data anomalies

Data Architecture & System Integration

• Design and maintain scalable data architecture connecting ERP (Infor M3), data warehouse, CRM, and external systems
• Build and manage data pipelines (ETL/ELT) to ensure timely and accurate data availability
• Enable seamless data flow across systems to support real-time and near-real-time decisions
• Standardize data models to support analytics and operational processes

MRP & Operational System Enablement

• Ensure MRP and planning systems are supported by accurate and structured data
• Partner with supply chain and operations to optimize lead times, safety stock, and planning parameters
• Identify and resolve data issues driving inefficiencies in purchasing, production, and inventory
• Support the evolution of MRP into a proactive, optimized planning system

Data Accessibility & Decision Enablement

• Build data models that make data accessible for analysts, data scientists, and business leaders
• Develop datasets that enable rapid analysis and insight generation
• Support dashboards, reporting tools, and self-service analytics capabilities
• Ensure key business metrics are consistently defined and trusted

Cross-Functional Collaboration

• Partner with Data Science to provide clean, structured datasets for modeling
• Translate business requirements into data architecture solutions
• Work with supply chain, operations, and finance leaders to prioritize data needs
• Serve as a bridge between technical systems and business applications

Transformation & Continuous Improvement

• Lead initiatives to modernize data infrastructure and capabilities
• Identify opportunities to automate manual processes and eliminate workarounds
• Drive transition toward a fully integrated, data-driven operating model
• Establish best practices for data engineering within the organization

Qualifications, Education and/or Experience

• Bachelor’s degree preferred (Data Engineering, Computer Science, Information Systems, or related field)
• Experience with data architecture, data pipelines, and system integration
• Experience working with ERP systems, data warehouses, and analytics platforms
• Strong understanding of data governance, data quality, and master data management
• Experience supporting supply chain, operations, or business analytics environments preferred
• Proficiency in data tools, SQL, and data modeling concepts
• Strong analytical and problem-solving skills
• Ability to translate business needs into technical solutions
• Experience working cross-functionally in a fast-paced environment