Senior Data Engineer

  • Overview

    Nordstrom is on a journey from legacy batch-centric practices to a real-time, event-streaming-centric platform: Nordstrom Analytical Platform (NAP), in order to produce high-quality pre-stitched 360 views of our customers, product, Inventory, etc.

    We are ready to take the next step in our journey and build business logic that delights our customers.

    Marketing Technology Streaming Team is tasked with using data to improve the customer experience and our ability to reach people in the way they prefer with relevant information to make their shopping experience more seamless.

    Senior Data Engineer will be a part of a key team of Nordstrom Technology Engineers that apply scientific and mathematical principles to design, build, and maintain technology products, systems, and solutions. These technology products and solutions provide E2E customer experiences while meeting the needs of the business.

  • Responsibilities

    Design and develop distributed data processing pipelines in the Big Data ecosystem using Python, Java, Kafka, S3, AWS Glue, Presto, Apache NIFI, etc.

    Lead the transitioning of our partners to our event-driven business model

    Turn data into insights and connect those insights with our customers

    Collaborate with technical analytics, and marketing business partners to build scalable and durable solutions that drive business outcomes

    Design, communicate and execute end-end solutions

    Continuously improve upon existing processes and solutions

    Ongoing production support of marketing data products

    Serve as a mentor in engineering culture

  • We Require

    • 4+ years of professional experience
    • 4+ years of experience in at least one programming language (Python, Java, Scala)
    • 4+ years of experience with MPP Databases, SQL, Data modeling, Data mining, and Automated engineering solutions
    • experience integrating with partners and becoming an internal SME on their integration (SalesForce, Liveramp, etc)
    • experience with distributed systems, like: Spark, AWS EMR
    • experience with AWS or Azure

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