Lead Data Engineer, Customer Identity Analytics (Hybrid - Seattle, WA)
About The Position
In the Data & Analytics Services organization, our teams build and maintain the data infrastructure that powers customer analytics, merchandising insights, and marketing measurement across Nordstrom. We help ensure customers receive a seamless, personalized experience across every channel by building the unified data assets that drive business decisions at every level of the company. Delivering great customer experiences — from relevant recommendations to accurate loyalty rewards to effective marketing — depends on a consistent view of our customers across channels. Our Customer Identity team maintains the platform that makes this possible, and this role will serve as its technical lead. As the Lead Data Engineer on the Customer Identity team, you will own the technical direction: hands-on with customer recognition systems and data quality analysis while also setting roadmap and strategy for the team. You’ll guide 4 engineers, with plans to grow the team as scope expands. You’ll own the full lifecycle of identity platform quality — from improving match accuracy to designing quality KPIs to modernizing our data platform architecture.
Requirements
- 7+ years of experience in data engineering, applied data science, or machine learning, with hands-on work in entity resolution, record linkage, or customer identity systems at scale
- Deep understanding of data matching concepts: match rules, blocking strategies, confidence thresholds, and precision/recall tradeoffs in customer data systems
- Production-quality SQL skills and fluency in BigQuery or a comparable cloud data warehouse, with hands-on experience in dbt, airflow or equivalent transformation frameworks
- Ability to frame ambiguous data quality problems as measurable experiments and communicate statistical concepts to business stakeholders
Responsibilities
- Own the strategy to improve customer recognition accuracy by working with upstream data partners, evaluating data enrichment approaches and piloting new techniques that help deliver more consistent and personalized experiences
- Collaborate with customer analytics leadership and business stakeholders to ensure the identity platform supports key use cases, from marketing measurement to customer lifetime value modeling to personalization
- Design and implement platform quality KPIs, match confidence scoring, precision/recall metrics, and reconciliation measures across identity methods to ensure accuracy and reliability
- Lead the migration of identity infrastructure from complex orchestration layers to a warehouse-native architecture (BigQuery + dbt), reducing operational overhead so the team can focus on analytical improvement
- Mentor and develop engineers on the customer analytics, setting technical standards, running design reviews, and providing direct feedback
- Maintain a high bar for data quality, testing, and monitoring, building automated checks that catch data quality regressions before they impact downstream reporting
Benefits
- Medical/Vision, Dental, Retirement and Paid Time Away
- Life Insurance and Disability
- Merchandise Discount and EAP Resources
- 401k, medical/vision/dental/life/disability insurance options, PTO accruals, Holidays, and more.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
