✦ Luna Orbit — Data & Analytics

Data Engineer 2 (Hybrid - Seattle, WA)

at Nordstrom

📍 Seattle, WA Hybrid 💰 $121K – $188K USD / year Posted March 13, 2026
Salary $121K – $188K USD / year
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
Category Data & Analytics

This role involves designing and developing scalable data pipelines and solutions to support real-time analytics at Nordstrom, leveraging cloud technologies and data engineering best practices.

  • Design scalable data pipelines
  • Optimize data performance
  • Collaborate with data analysts and scientists
  • Implement CI/CD pipelines
  • Support production data systems

The technical environment includes programming in Python and Java, working with GCP BigQuery, data modeling, data mining, and implementing CI/CD pipelines within a cloud-based data ecosystem.

The ideal candidate is a mid-level data engineer with 3+ years of experience in data pipelines, data modeling, and cloud platforms like GCP. They are creative, collaborative, and customer-focused, with strong programming skills in Python and Java.

PythonJavaSQLData pipelinesData modelingGCP BigQuery
TeradataCloud computingData miningCI/CD
GCPBigQueryTeradataCI/CD tools
PythonJavaSQLBig DataData pipelinesGCPBigQueryData modelingData miningCI/CDCloud computingData analysisSoftware engineering principles
PythonJavaSQLBig DataData pipelinesGCPBigQueryData modelingData miningCI/CDCloud computingData analysisSoftware engineering principles
collaborationcommunicationproblem-solvingcreativitycustomer-driventeamwork
Industry Retail / E-commerce / Data Analytics
Job Function Developing and maintaining data pipelines and analytics solutions
Data EngineerPythonJavaSQLBig DataData pipelinesGCPBigQueryData modelingData miningCI/CDCloud computingData analysisSoftware engineering principlesData Engineer 2GCP BigQuerySoftware engineering

Lack of experience with GCP BigQuery, Less than 3 years of data engineering experience, No experience with data pipelines or data modeling

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