Data Engineer, WW Pricing - Data & Analytics

Amazon is hiring a Data Engineer, WW Pricing - Data & Analytics in Seattle, United States. It pays $132k-$179k a year and Level rates it ; you can apply on Level.

AI in this role

Build large-scale data pipelines, ML data infrastructure, and GenAI solutions to support pricing algorithms and analytics.

awsredshiftkinesisemrlambdasqlgenai

data-engineeringetldata-modelingbi-analytics

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 Data Engineer, 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 be developing GenAI based solutions to improve the operational and reporting efficiency.

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
- 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

Basic qualifications

- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
- Experience with data modeling, warehousing and building ETL pipelines

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually

How we rate this

Data Engineer, WW Pricing - Data & Analytics at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Data Engineer, WW Pricing - Data & Analytics is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $132k-$179k a year.
The role is based in US, WA, Seattle.
The job was posted on October 9, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringETLData ModelingBi AnalyticsAWSRedshiftKinesisEmr

Also common in data engineer jobs at this level

Python Spark Machine learning Airflow Azure Databricks

Pay

This job starts at: $132k
Typical data engineer job: $146k

This posting starts 10% below the typical data engineer job. See data engineer jobs

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where bi analytics was part of your work. What did you do?
Walk me through how you've used AWS in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Data Engineering, ETL, Data Modeling, Bi Analytics, and AWS. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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