Senior Data Engineer, Insights Delivery Merch

Nordstrom

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Seattle, WA
Salary: $142,000–$220,500 / yr
Posted: 10 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $171k

This role $181k

$120k most similar roles pay here $231k

This role pays more than 52% of similar roles. Most pay $131,103–$211,200 — the shaded band above. At the midpoint, this role pays about $181k versus about $171k 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 33 open roles on FindRole.

Listed pay typically runs $142,000–$220,500 across 32 roles with salary data.

Most-posted roles

View all roles at Nordstrom

At a glance

TL;DR · Senior Data Engineer, Insights Delivery Merch

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Senior Data Engineer, Insights Delivery Merch joins the Insights Delivery Merch team to develop scalable software applications, data pipelines, and database solutions for the Nordstrom Data Platform. This role involves designing distributed data processing pipelines within a Big Data ecosystem in the cloud, performing code reviews, building testing tools, and managing CI/CD pipelines. The engineer will also focus on identifying performance issues, maintaining high data quality standards, and providing production support while leveraging AI to accelerate development velocity. Key technical requirements include proficiency in Java or Python, SQL, and data modeling, alongside experience with Kafka, Flink, Spark, DynamoDB, Airflow, and GCP BigQuery. The role addresses the specific business needs of merchandise planning and inventory systems by delivering near real-time, pre-stitched 360 views of products, inventory, purchase orders, price, fulfillment, logistics, and customer service data.

What does a Data Engineer earn?

Median $170950 from 215 postings across 56 companies.

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Skills

Python Java SQL GCP BigQuery Kafka Flink Spark DynamoDB Airflow dbt CI/CD Data Modeling Distributed Systems event-streaming Big Data Agile

What you'll do

Design and develop scalable data analytical solutions using modern technologies in an agile environment.
Build distributed data processing pipelines within the Big Data ecosystem in the cloud.
Lead projects and mentor junior engineers to ensure high engineering standards.
Conduct code reviews and enforce software engineering principles across the team.
Develop testing tools and CI/CD pipelines to reduce automation friction.
Identify, measure, and maintain high data quality standards across all solutions.
Perform production support duties to resolve incidents and manage logging dashboards.
Leverage AI tools to accelerate development velocity and automate production support.

What we're looking for

Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.
2+ years of experience leading multi-engineer projects and mentoring junior engineers.
5+ years of experience designing robust data pipelines, relational and non-relational database architectures.
5+ years of experience in at least one modern programming language such as Java or Python.
5+ years of experience with databases, SQL, data modeling, and automated engineering solutions.
3+ years of experience with cloud environments such as GCP.
1+ year of experience in developing near real-time distributed data processing solutions using Kafka, Flink, Spark, DynamoDB, and Airflow.
1+ year of experience in scalable distributed systems and event-driven streaming architecture.
1+ year of experience using AI-powered development tools to accelerate coding workflows and automate testing.
Familiarity with data build tools such as DBT (preferred).
Familiarity with GCP BigQuery (preferred).
Business domain knowledge in Merchandise Planning, Inventory and Selling Control reporting data solutions (preferred).

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