Senior Engineer, Merchandise Planning

Nordstrom

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Seattle, WA
Salary: $166,000–$258,000 / yr
Posted: 16 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $184k

This role $212k

$130k most similar roles pay here $272k

This role pays more than 76% of similar roles. Most pay $155,900–$212,000 — the shaded band above. At the midpoint, this role pays about $212k versus about $184k for comparable roles.

Based on 240 similar postings.

Employer

About Nordstrom

Nordstrom is a leading American luxury department store chain offering a wide selection of clothing, shoes, accessories, and beauty products through its stores, Nordstrom Rack outlets, and online. Industry: Luxury Department Store Retail

Nordstrom currently has 30 open roles on FindRole.

Listed pay typically runs $142,000–$220,500 across 29 roles with salary data.

Most-posted roles

View all roles at Nordstrom

At a glance

TL;DR · Senior Engineer, Merchandise Planning

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Senior Engineer 2, Merchandise Planning joins a specialized team focused on modernizing platforms for financial planning, assortment planning, item planning, and demand forecasting. This role involves designing, building, and operating data integration pipelines to connect a SaaS-based planning platform with enterprise systems and data warehouses. The engineer will develop analytics and reporting tools, manage data quality and observability, and integrate AI agents to automate workflows. Key technical requirements include proficiency in Python, Spark, and Apache Airflow for orchestrated pipelines; BigQuery for building curated datasets and semantic models; and Looker for delivering insights. Candidates must possess strong SQL skills, experience with RESTful APIs, and familiarity with tools like Docker and CI/CD pipelines. The role addresses the complex challenge of unifying merchandise planning and open-to-buy data into a reliable, scalable system to support critical business decisions.

What does a Engineer earn in Washington?

Median $174600 from 40 postings across 12 companies.

See salary data

Skills

Python Apache Airflow Apache Spark BigQuery Looker SQL RESTful APIs Docker CI/CD GCP AWS Azure PostgreSQL MySQL MongoDB Redis Data Modeling

What you'll do

Design, build, and operate data integration platforms using Airflow, Python, and Spark to move data between systems.
Develop analytics and reporting by building curated datasets and semantic models in BigQuery and Looker.
Configure and extend SaaS planning applications to support merchandise, assortment, item, and forecasting workflows.
Design and ship AI agents to automate and augment planning and data workflows.
Ensure data quality, reconciliation, and observability for the integration platform through monitoring and alerting.
Lead technical decision-making and influence priorities by collaborating with cross-functional business stakeholders.
Mentor junior engineers by breaking down complex tasks and promoting AI-enabled software development practices.
Participate in rotating 24/7 shifts to provide production support, bug fixes, and system enhancements.

What we're looking for

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 focus on data and integration engineering.
Proficiency in building batch and orchestrated pipelines using Apache Airflow, Python, and Apache Spark.
Expertise in cloud data warehouses like BigQuery for building curated datasets and data models.
Strong SQL skills and experience designing schemas and transformations for analytics and reporting.
Experience developing and consuming RESTful APIs and integrating third-party or SaaS applications.
Proficiency with relational databases (PostgreSQL, MySQL) and familiarity with NoSQL databases (MongoDB, Redis).
Practical experience using AI coding tools to accelerate development and improve code quality.

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