Lead a team of engineers building and operating the event-driven pipelines and cloud data warehouse products that power product, pricing, vendor, and promotions data across Nordstrom
Own the enterprise product dimension layer
tens of millions of items across the full product hierarchy
consumed by machine learning, personalization, and downstream reporting teams
Drive the brand partner data program: engineering the data feeds that onboard and sustain external brand partners onto Nordstrom's platform
Deliver pricing and promotions data capabilities
pricing analytics, promotional event data, campaign-specific reporting views
in close partnership with merchandising and marketing stakeholders
Lead platform modernization: medallion architecture migration, observability and monitoring tooling, data governance, and cloud infrastructure across a portfolio of event consumer services
Partner with stakeholders across machine learning, digital product, compliance, partner programs, and supply chain to translate business requirements into scalable data products
Contribute to architecture and design decisions
this is a hands-on role with real technical depth expected
Recruit, develop, and retain engineering talent; provide direct feedback and coaching to help engineers grow
Promote DevOps best practices: CI/CD, infrastructure-as-code (Terraform), monitoring, alerting, and incident response

5+ years of relevant software engineering experience, with strong foundations in event-driven systems, distributed data pipelines, or enterprise data products
2+ years of experience managing engineering teams
Hands-on experience with messaging technologies and patterns
Kafka and/or Confluent Cloud strongly preferred
Proficiency with Java and/or Java Spring Boot for building microservice consumers
Experience building and operating data products in a cloud data warehouse (BigQuery, Snowflake, or similar)
Experience with cloud infrastructure (AWS and/or GCP) and infrastructure-as-code (Terraform)
Strong understanding of DevOps best practices including CI/CD, containerization (Docker/Kubernetes), monitoring, and production support
Proven ability to ship reliable, scalable systems with high data quality standards
BA/BS in Computer Science or closely related field, or equivalent practical experience

Engineering Manager – Product & Vendor Insights

Key skills