Data Analyst - Insights Delivery Merchandising Analytics

The Insights Delivery - Merchandising Analytics team enables data-driven decision-making across Nordstrom's merchandising organization by developing and maintaining scalable analytics solutions, data pipelines, and self-service reporting products.

Our team partners with Merchandising, Planning, Finance, Stores, Digital, Inventory, and cross-functional technology teams to deliver trusted, actionable insights that support critical business decisions. We leverage modern data technologies, including Google Big Query, Looker/LookML, SQL, DBT and Airflow, to build reliable data products, streamline reporting processes, and improve access to business-critical information. You'll work across a portfolio of 60+ reports that merchant buyers and business leaders rely on to decide what to buy, how much to spend, and when to mark down.

Our pipelines are modern and up to date, and we use AI throughout our work to move faster.

As a Data Analyst 3 - Insights Delivery Merchandising Analytics, you'll play a key role in designing, developing, and maintaining analytics solutions that support Nordstrom's merchandising and planning operations.

You'll own analytics deliverables end-to-end, from gathering business requirements and developing data models to building reporting solutions, validating data accuracy, and supporting production workflows.

This is a hands-on technical role that requires strong SQL and data pipeline expertise, experience with business intelligence tools, and the ability to translate complex business requirements into scalable, reliable analytics products.

You'll collaborate with business stakeholders, data engineering teams, and fellow analysts to modernize reporting capabilities, enhance self-service analytics, and continuously improve data quality and operational efficiency.

• Design, develop, and maintain scalable data pipelines, analytical datasets, and reporting solutions using SQL, Google Big Query, Looker, and LookML.
• Build and enhance Looker Explores, semantic data models, dashboards, and self-service reporting solutions to support merchandising analytics and business decision-making.
• Partner with Merchandising, Planning, Finance, and other cross-functional stakeholders to gather requirements, define business metrics, and translate analytical needs into technical solutions.
• Develop and support analytics products across key merchandising functions, including merchandise financial planning, supplier and category planning, open-to-buy, inventory, markdowns, sales performance, and holiday reporting.
• Contribute to reporting modernization initiatives, including migrating legacy Tableau reporting solutions to Looker, rebuilding merchandise planning reports to align with our new planning system, metrics, and planning methodology, and improving the scalability, consistency, and usability of analytics products.
• Build, maintain, and troubleshoot data transformation and orchestration workflows using Airflow, DBT, and cloud-based data platforms.
• Use AI tools to accelerate requirements discovery, understanding of systems and data, and the development and review of data pipelines and reports.
• Ensure data accuracy, consistency, and reliability through comprehensive testing, reconciliation, validation, and performance optimization.
• Collaborate with data engineering and upstream data teams to investigate data discrepancies, resolve pipeline dependencies, and improve data availability.
• Participate in code reviews, version control workflows, technical documentation, and development best practices to maintain high-quality, reusable analytics solutions.
• Monitor and support production reporting processes, troubleshoot issues, and respond quickly to high-visibility production issues, with occasional extended hours when needed, to ensure business continuity.
• Identify opportunities to automate manual reporting processes, improve query performance, and enhance self-service analytics capabilities.
• Independently manage assigned deliverables, communicate project progress and risks, and collaborate with senior team members on complex or cross-functional initiatives.

• Bachelor's degree in computer science, Information Systems, Data Analytics, Statistics, Mathematics, Engineering, or a related field, or equivalent practical experience.
• 4+ years of professional experience in data analytics, business intelligence, analytics engineering, or related technical field.
• Advanced SQL skills, including…