Senior Engineer 2, Merchandise Planning - (Hrbrid, Seattle)

Nordstrom•Seattle, WA

1d•$166,000 - $258,000•Hybrid

About The Position

As a Senior Engineer 2, you'll be part of a key team of Nordstrom Technology professionals who apply scientific, mathematical, and social principles to design, build, and maintain technology products, systems, and solutions which provide amazing customer experiences while meeting the needs of the business. At this level, you are responsible for the quality of a team's work, ensuring that all designs are clear and complete for successful execution. You undertake complex design and problem-solving without supervision. About Merchandise Planning: We implement and modernize the platforms that power how Nordstrom plans its business across Merchandise (Financial) Planning, Assortment Planning, Item Planning, and Demand Forecasting. We are enabling a SaaS-based planning platform that unifies merchandise planning, open-to-buy, assortment, and allocation so that merchants, planners, and finance can plan using AI-driven demand forecasting. This platform depends on a robust data integration layer that moves data in and out of the application reliably and at scale, and on analytics and reporting that turn planning data into decisions. As a Senior Engineer 2 on the Merchandise Planning team, you will be instrumental in realizing this vision. You will own the quality of a team's work, focusing primarily on data and integration engineering — designing, building, and operating the pipelines that connect the planning platform to Nordstrom's enterprise systems, data warehouse, and downstream consumers. You will enable and extend the SaaS planning application, build and maintain the data integration platform that supports data flowing in and out of it, and develop analytics and reporting that support planning and forecasting decisions. You will also help set the team's AI direction by adopting AI-enabled software development in your everyday workflow and by designing and shipping AI agents that automate and augment the planning and data workflow.

Requirements

Bachelor's or master's degree in an engineering discipline, preferably computer science, or equivalent.
8+ years of professional experience delivering quality software, with a strong focus on data and integration engineering.
Strong proficiency in data pipeline and integration engineering: hands-on experience building batch and orchestrated pipelines with Apache Airflow, Python, and Apache Spark.
Cloud data warehouse expertise: proficient with BigQuery (or a comparable warehouse) for building curated, performant datasets and data models.
Strong SQL and data modeling skills, with experience designing schemas and transformations for analytics and reporting use cases.
API and integration skills: experience designing, developing, and consuming RESTful APIs and integrating third-party and SaaS applications, including handling data in and out via APIs, files, and events.
Experience enabling, implementing, or integrating enterprise SaaS planning or supply chain platforms such as Toolio, O9, Anaplan, Blue Yonder, or similar.
Analytics and reporting experience, including developing reporting/dashboards, ideally in Looker or a comparable BI platform.
DevOps and deployment: familiar with CI/CD pipelines, Docker, cloud services (GCP, AWS, or Azure), and deployment best practices.
Practical experience with AI-assisted software development using AI coding tools (e.g., Claude, Claude Code, GitHub Copilot) to accelerate development and improve code quality and data validations.
Database management: proficient with relational databases (PostgreSQL, MySQL) and familiar with NoSQL databases (MongoDB, Redis).
Problem-solving and debugging: strong analytical skills with the ability to troubleshoot and resolve data, integration, and application issues efficiently.
Agile and team collaboration: experience working in Agile/Scrum environments, collaborating with cross-functional teams including analysts, testers, and product managers.
Experience with system design, architecture, scaling, and performance testing for data-intensive systems.
Strong understanding of computer science fundamentals.

Nice To Haves

Domain knowledge of merchandise planning, assortment planning, item planning, or demand forecasting is a strong plus, especially within fashion retailing.

Responsibilities

Develop innovative solutions to drive Nordstrom's business, demonstrating competence in engineering concepts and theories and combining them with business understanding to design, document, and implement clean, robust, and scalable data and integration solutions to complex planning and forecasting problems.
Design, build, and operate the data integration platform that moves data in and out of the SaaS planning application, building and maintaining batch and orchestrated pipelines using Airflow, Python, and Spark to integrate with Nordstrom systems.
Enable, configure, and extend the SaaS planning platform to support Merchandise Planning, Assortment Planning, Item Planning, and Forecasting workflows, partnering closely with the vendor and business to translate planning requirements into reliable technical solutions and configurations.
Develop analytics and reporting on top of the planning data — building curated datasets and semantic models in BigQuery and delivering reporting in Looker to support planning, forecasting, and adoption insights.
Collaborate with other engineering teams, business stakeholders, and program and product managers across Merchandising, Planning, Finance, and Supply Chain to make technical decisions and influence priorities and trade-offs that achieve short- and long-term business objectives.
Own data quality, reconciliation, and observability for the integration platform, building monitoring, alerting, and validation so that data between systems is timely, accurate, and trusted.
Contribute toward moving the team forward in engineering practices such as continuous integration, continuous delivery, cloud migration, test-driven development, and AI-enabled software development.
Champion an AI-enabled approach to software development throughout the development process — from intake and development to code review and testing — to accelerate velocity, raise the quality bar, and help more junior engineers adopt these tools effectively.
Design, develop, and ship AI agents that support Merchandise Planning, including their evaluation, observability, and human-in-the-loop guardrails.
Assist engineering manager(s) with planning, analysis, and definition of high-level software and data strategies and solutions through functional knowledge and an understanding of the enterprise business systems and industry.
Take ownership of systems or designs that span multiple people's work, breaking work into smaller tasks for more junior engineers to support.
Keep current with industry trends and new technologies, applying them to the team's architectural needs, and ensure corporate policies and industry best practices are observed and followed in developed applications.
Transition from application development to support as needed, participate in rotating 24/7 shifts to support developed products, and work with business, infrastructure, and security teams to deliver enhancements and bug fixes for production systems.