Senior Analytics Engineer, Fullscript

• This is a senior, hands-on role for someone who thrives working across data modeling and operational systems, building reliable, production-grade data infrastructure that supports real-world operations
• 5+ years of experience in analytics engineering, data engineering, or advanced operational analytics
• Strong proficiency in SQL and deep comfort working in modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift)
• Hands-on experience building and maintaining transformation layers using dbt or similar ELT tools
• Strong understanding of data modeling concepts including grain, fact tables, dimensions, and schema design
• Experience working with operational, warehouse, logistics, fulfillment, or supply chain datasets in a execution-heavy environments
• Experience building production-grade data models that support performance monitoring and operational decision-making
• Ability to translate complex workflows into structured, measurable metrics
• Comfort partnering directly with operational leaders and senior stakeholders

Desirable

• We’re looking for a Senior Analytics Engineer, Operations & Distribution to partner closely with our Distribution Center (DC) Operations and Customer Experience teams to build and own the data foundations that power operational performance
• This role sits within our Analytics & Data Science organization and supports DC Operations, Customer Support, and Customer Experience leadership. You will be responsible for designing and maintaining the backend data models that enable leaders to monitor workforce productivity, throughput, service levels, cost efficiency, and fulfillment quality
• Unlike traditional analytics roles focused primarily on analysis or reporting, this role is centered on building durable, trusted data infrastructure that becomes the backbone of operational decision-making
• Build and own core operational data models in our enterprise data warehouse that power DC performance tracking and operational monitoring
• Design scalable transformation logic using dbt and SQL to support use cases such as hourly employee activity tracking, throughput analysis, labor productivity, and composite performance models (e.g., “perfect order” frameworks)
• Partner directly with DC Operations and Customer Experience leaders to translate operational workflows into measurable, reliable data assets
• Define and implement trusted metrics for operational efficiency, service quality, workforce performance, and fulfillment reliability
• Ensure operational data pipelines are tested, documented, and production-grade (balancing performance, scalability, and long-term maintainability)
• Support deeper modeling efforts (e.g., capacity planning, forecasting, optimization) in collaboration with Data Science partners
• Act as a senior technical voice for operational analytics engineering, influencing modeling standards, patterns, and best practices
• Operate independently as the primary data infrastructure owner for operational performance initiatives