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Data Engineer - Customer Insights Delivery; Hybrid - Seattle, WA

Job in Seattle, King County, Washington, 98127, USA
Listing for: Nordstrom
Full Time position
Listed on 2026-06-04
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 85000 - 110000 USD Yearly USD 85000.00 110000.00 YEAR
Job Description & How to Apply Below
Position: Data Engineer 2 - Customer Insights Delivery (Hybrid - Seattle, WA)
as the core of our analytics engineering stack, investing in a semantic layer, and expanding the role of AI in how our pipelines are built and This role reports to the Senior Engineering Manager, Customer Insights Delivery, and partners day-to-day with Customer Analytics, Marketing, and Customer Care teams. You will join a team of 12, with hands-on opportunities to contribute to the dbt migration of around 40 critical pipelines across domains and semantic-layer work alongside more senior engineers as you grow in the role.
* Read this first:
* would be a good fit for the position. Nordstrom is an equal-opportunity employer. We are building a diverse, inclusive workforce and hope you will join us.
** This role is offered as hybrid in Seattle, WA. Candidates must be available to work in office at the Nordstrom corporate headquarters a minimum of 4 days/week to be considered for this position.
** We encourage you to apply even if you do not meet all the qualifications but feel you Participate in code reviews, apply data engineering best practices (dbt testing, documentation, lineage, performance, and cost), and grow your skills through feedback from senior engineers. of experience building models, or strong familiarity with 1+ year of experience in at least one modern programming language such as Python or Java.
1+ year of experience with data modeling and data warehousing.

Curiosity about applying AI and ML to data engineering and business problems, and a passion for operational excellence and customer impact.

Experience with semantic layer tools such as Looker.

Experience with Airflow or similar orchestration tools.

Familiarity with distributed data processing tools such as Kafka or Spark. Useful context, though not central to this role.

Experience using LLM-assisted tools such as Claude Code or Cursor in an analytics workflow.
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