Nearly a year ago, we began our journey to transform our approach to data and analytics from a batch-centric platform with siloed data marts, to our Nordstrom Analytical Platform (NAP), a real-time, event-streaming-centric, analytical platform that provides high quality, pre-stitched 360 views of our customers, products, inventory, customer service, fulfilment/logistics, and credit. The Nordstrom data team designs, develops and maintains software applications and services that support all of Data Engineering and Analytics business needs to drive the Nordstrom Omni channel experiences. This opportunity also provides various avenues to collaborate and influence several other platforms within Nordstrom Technology and have a company-wide impact - both business and engineering. Data Analytics is a strategic focus area for the company.\\n\\nOver the next year we will be focused on data integration across all Nordstrom brands to create a holistic view of the customer & products, enabling us to personalize their experience and engagement with Nordstrom to reflect their unique preferences and style. Delivering real-time data will be central to ensuring that they receive only the most relevant information and have a seamless online and offline experience.\\n\\nA day in the life...\\n\\nDesign and develop at the organization level event driven mico-services architecture for real time analytics.\\n\\nDesign and develop at the organization level distributed data processing pipelines in the Big Data ecosystem using Spark, Flink, Kafka, Hive, Presto, etc.\\n\\nLead projects across a global team. Drive key technical and design discussions with technical leads across the engineering organization\\n\\nMake sound technical decisions, influence priorities, and come up with tradeoffs that maps to short-term and long-term goals and objectives\\n\\nChampions new techniques and influence engineering standards across the organization\\n\\nCollaborate with technical program management, analytics, and marketing business partners to build scalable and durable solutions that drive business outcomes\\n\\nBuild data products that reduce friction and time to delivery for Data Scientists and Analysts\\n\\nDesign, communicate, and execute end-end solutions\\n\\nContinuously improve upon existing processes and solutions\\n\\nOngoing production support of data products\\n\\nServe as mentor to other engineers\\n\\n\\nYou own this if you have: \\n\\n8+ years of professional experience\\n\\n8+ years of experience in at least one programming language (e.g. Python, Java, Scala)\\n\\n8+ years of experience with MPP Databases, SQL, data modeling, data mining, and automated engineering solutions.\\n\\nStrive to deliver results, make quality technical decisions, manage complexity, and drive a vision while being customer focus.\\n\\nExperience with standard industry practices for engineering and operational excellence\\n\\nExperience with distributed systems (Spark, AWS EMR etc)\\n\\nExperience with Spring boot framework\\n\\nExperience with cloud environments (AWS or other equivalent cloud providers)\\n\\nExperience in developing near real-time data processing solutions using Kafka, Flink, Spark Streaming (preferred)\\n\\nBachelor's in Computer Science, Engineering, or equivalent practical experience (Master's preferred)\\n\\nThis range may vary for candidates hired to work in locations other than Colorado.\\n\\nMinimum = $124,600/annually\\n\\nMaximum = $186,900/annually
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- Medical/Vision, Dental, Retirement and Paid Time Away
- Life Insurance and Disability
- Merchandise Discount and EAP Resources
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The job posting highlights the most critical responsibilities and requirements of the job. It's not all-inclusive. There may be additional duties, responsibilities and qualifications for this job.
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