Data Analyst 3 - Insights Delivery Merchandising Analytics

Job Description 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 BigQuery, 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. The Role 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. A Day in the Life… • Design, develop, and maintain scalable data pipelines, analytical datasets, and reporting solutions using SQL, Google BigQuery, 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. You Own This If You Have… • 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 complex joins, window functions, common table expressions (CTEs), aggregations, and query performance optimization. • Hands-on experience building and maintaining ETL/ELT data pipelines, including job scheduling and orchestration, using technologies such as Apache Airflow and/or dbt. • Hands-on experience working with cloud-based data warehouses, preferably Google BigQuery. • Experience developing and maintaining business intelligence solutions using Looker/LookML, Tableau, or comparable reporting platforms. • Experience building analytical data models, reusable reporting datasets, dashboards, and self-service analytics solutions. • Familiarity with Git-based version control, code reviews, and collaborative software development practices. • Strong analytical and problem-solving skills, with the ability to investigate data discrepancies, troubleshoot technical issues, and identify root causes. • Demonstrated ability to translate ambiguous business questions into structured technical requirements and actionable reporting solutions. • Experience collaborating with both technical and non-technical stakeholders and communicating complex data concepts clearly. • Ability to independently manage multiple deliverables, prioritize competing requests, and consistently deliver high-quality solutions. • Strong attention to detail, commitment to data accuracy, and willingness to contribute to production support and continuous impro