Sr. Data Engineer, Nordstrom Analytical Platform (Hybrid)

Job Description

Nordstrom Analytical Platform (NAP) is a real-time, event-streaming-centric analytical platform that provides high-quality, pre-stitched 360 views of our customers, products, inventory, customer service, fulfillment, logistics and credit. The Insights Delivery Team delivers data and insights that enables Nordstrom data analysts, data scientists, leadership, store personnel and other business users to drive the critical Nordstrom customer experiences in a single place near real-time. 

On our team, you will own the design and development of highly scalable software applications, services, data pipelines and database solutions, apply scientific, mathematical and social principles, and deliver on the Nordstrom strategic visions. You will have various avenues to collaborate and influence several other platforms within Nordstrom Technology and have a companywide impact on both business and engineering. The ideal candidate is creative, customer-driven and has a passion for data engineering and products. 

Read this first: We encourage you to apply even if you do not meet all the qualifications but feel you 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! 

A day in the life...

• Design and develop scalable and durable data analytical solutions using in-house and modern technologies for business in an agile environment. 

• Understand the specific needs of a major line of business and the related set of applications, systems, or functions. 

• Design and develop distributed data processing pipelines in the Big Data ecosystem in the Cloud, apply data concept, modeling, structures, and infrastructure technologies and adhere to good engineering practices. 

• Split larger designs into smaller work units and mentor other engineers across a wide spectrum of activities.  

• Own implementation of engineering standards, quality assurance standards and security features.  

• Own responsibility for code reviews and drives accountability in following software engineering principles.  

• Build testing tools and CI/CD pipeline, reduce automation friction to speed up the path to business outcomes. 

• Identify data performance issues and optimize the solution. 

• Perform on-going production support and on-call support duties. Work with both Onsite and offshore resources daily to resolve any incidents and issues.  

• Responsible for cost savings, production notifications, alerts, and logging dashboards. 

• Collaborate with product managers, data analysts, data scientists, business partners and other tech teams. 

• Partner with analyst stakeholders toward delivering highly effective self-service