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Sr. Data Engineer, WW Pricing Data and Insights

Summary

Senior Data Engineer leading the design of data pipelines, ML infrastructure, and BI solutions for Amazon's global pricing systems using AWS services and GenAI.

WW Pricing drives the success of Amazon Retail and 3P Pricing. We build software that makes billions of monthly pricing recommendations on our marketplaces. We earn our customers' trust by consistently delivering the lowest prices possible: we price and publish prices automatically for the millions of products bought worldwide every day by our customers.

You will be joining WW Pricing Data & Analytics team which consists of several Data Engineers and Business Intelligence Engineers.

As a Senior Data Engineer, you will be a technical lead on the team, leading designs and mentoring engineerings on the team. you will create data models and ML data infrastructure that power our pricing algorithms and shape both customer and seller experiences. You'll develop essential data flows that keep our systems running smoothly while uncovering valuable insights that drive customer and seller success. You'll leverage GenAI to build next generation solutions for data and analytics as well as operations.

This job is for you if you are passionate about working with the largest and most complex data to optimize service performance. You will own the models and processes for collecting and transforming data, and work within the Pricing software engineering teams to drive the resulting business initiatives. You will learn the customer's intentions, and support us in understanding them as we take our business to the next level.

Key job responsibilities
- Architecture design and implementation of next generation data pipelines and BI solutions
- Build next generation data and analytics solutions using GenAI
- Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
- Build and deliver high quality data architecture and pipelines to support business analyst, data scientists, and customer reporting needs.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

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