Global Customer Fulfillment (GCF) is seeking a Data Engineering Manager to lead the Quantitative Business Intelligence Tools (QuBIT) team in delivering enterprise-scale data solutions across our fulfillment network. You will manage a high-performing team of Data Engineers (DE) and Business Intelligence Engineers (BIE) while architecting solutions that provide seamless data access across hundreds of fulfillment centers shipping millions of packages annually. Every shipment represents an opportunity to improve customer service and pricing through data-driven insights.
As the QuBIT team leader, you'll establish data engineering excellence and democratize data access through scalable BI solutions. You'll oversee both complex data engineering initiatives and business-critical reporting solutions while standardizing reporting frameworks to transform raw data into actionable insights. The role combines strategic data architecture with hands-on leadership, managing teams that build scalable reporting and analytics solutions, implement automation initiatives, and own key business metrics.
You'll develop and prioritize project roadmaps as your team creates complex analytics solutions at scale, focusing on operational excellence. Working closely with senior leaders and PMs, you'll influence strategic decisions and drive data-informed decision making throughout the network, engaging with leadership across all organizational levels from fulfillment centers to corporate offices.
Key job responsibilities
Lead data engineering strategy, manage team of engineers, architect solutions, and partner with senior leadership to align technical initiatives with business objectives
Design and implement enterprise data warehouse solutions, ETL processes, and data lake architectures while establishing data quality/governance standards
Drive analytics excellence through automated reporting (MBR/QBR/WBR), BI tools implementation, and deep-dive analyses to deliver actionable business insights
Develop scalable data solutions, optimize data models, automate reporting pipelines, and implement self-service capabilities to support growing business demands
Partner with Engineering teams on data integration, maintain technical excellence, guide new technology adoption, and ensure high-quality solution delivery
Build strong cross-functional relationships, communicate effectively across organizational levels, and drive data-informed decision making throughout the company
