Supply Chain Analytics Engineer II

At DICK’S Sporting Goods , we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve. If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today! Overview The Analytics Engineer II bridges business operations, Data Engineering, and Business Intelligence by applying knowledge of Supply Chain processes, system workflows, and data relationships to develop trusted data products, scalable semantic models, and AI-enabled analytical capabilities. The role is responsible for the transformation, modeling, quality, documentation, delivery of governed business-ready data assets that provide a trusted foundation for reporting, self-service analytics, operational decision-making, and AI-enabled solutions. The role partners with Data Engineering on data ingestion and platform capabilities and supports downstream analytics teams through reliable data products, governed definitions, and technical knowledge transfer. Data Products & Analytics Solutions Partner with business stakeholders, Product, and Data Engineering teams to understand Supply Chain operations, business processes, system workflows, and data requirements. Translate business needs into scalable analytics solutions that support operational decision-making and align with business objectives. Design, build, maintain, and enhance curated datasets, semantic models, and reusable analytical products that provide a trusted foundation for reporting, self-service analytics, operational decision-making, and AI-enabled solutions. Apply SQL, data transformation techniques, business logic, and data modeling practices to integrate, validate, and transform complex data into trusted, governed, and business-ready information assets that accurately reflect business processes and system workflows. Develop and maintain semantic layers, certified datasets, governed metrics, and business definitions that promote reporting consistency, improve data accessibility, and reduce duplication across analytics solutions. Prepare and optimize analytical data products, semantic models, governed business definitions, and data experiences that support AI-enabled and conversational analytics, predictive insights, and other emerging data-driven capabilities. Contribute to AI-enabled analytics use cases through semantic preparation, prompt development, and output validation, in partnership with appropriate technical and governance teams. Data Quality, Governance & Reliability Apply established standards for data quality, performance, and governance across analytical data products. Leverage business process, system, and technical knowledge to execute test plans, validate source-to-target data flows, assess data quality, and validate analytical solutions. Document, communicate, and resolve identified issues using standardized testing methodologies. Maintain business and technical metadata, source-to-target mappings, data lineage, ownership information, technical specifications, and supporting documentation within approved data catalog and knowledge management tools to improve discoverability, auditability, governance, and change-impact analysis.Apply enterprise data-classification, privacy, security, access-control, and retention requirements to analytical datasets, semantic models, and self-service analytics solutions. Partner with appropriate security, privacy, and governance teams to ensure compliance with established standards. Monitor assigned data products in production, triage data quality and reliability incidents, support recovery and escalation activities, communicate identified business impact, document root causes, implement corrective actions and contribute to preventive reliability improvements. Assess upstream and d…

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