Data Engineer 2, Customer Insights Delivery (Hybrid - Seattle, WA)
About the position The Customer 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. In 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. 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. Understand architecture and able to design interaction between multiple modules. 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. 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. Influence quality standards, identify and measure across the entire 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 BI solutions. Communicate clearly and efficiently with our partner teams.
Responsibilities
- 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.
- Understand architecture and able to design interaction between multiple modules.
- 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.
- 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.
- Influence quality standards, identify and measure across the entire 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 BI solutions.
- Communicate clearly and efficiently with our partner teams.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
- 3+ years of experience in at least one modern programming language such as Java or Python
- 2+ years of experience with databases, SQL, data modeling, data mining, and automated engineering solutions.
- Experience with cloud environments such as AWS or GCP
- Experience in developing distributed data processing solutions using Kafka, Flink, Spark, Kubernetes, Airflow, or similar technologies.
- Experience in scalable distributed systems, service-oriented and event-driven streaming architecture
- Experience with best practices for data engineering and operational excellence
- Passion for innovative technologies, eagerness to learn and embrace an AI-first development approach, operational excellence, and customer impact
Nice-to-haves
- Familiarity with GCP BigQuery and Looker is a plus
- Experience with dbt is a plus
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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