Amazon Data Engineer

Job Details

Posted date: Jul 18, 2025

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Location: Seattle, WA

Estimated salary: $138,100
Range: $91,200 - $185,000


Description

We're building the next generation of data platforms, ML feature stores and analytical solutions that power pricing and promotions across Amazon.com. As a Data Engineer on our team, you'll architect and develop scalable solutions that impact millions of customers and billions in revenue. If you're excited by complex technical challenges and want to work at unprecedented scale, we want to talk to you.

Join our Pricing & Promotions Science, Data and Insights team, where you'll have the opportunity to continuously improve the systems that enable Amazon's annual worldwide revenue of billions of dollars.

Key job responsibilities

- Design, build, and operate highly scalable, fault-tolerant data processing systems using modern AWS services like Redshift, S3, Glue, EMR, Kinesis, and Lambda, and orchestration systems using Airflow

- Leverage your expertise in Python, Scala, or other modern programming languages to develop custom data processing frameworks and automation tools

- Collaborate closely with data scientists, analysts, and product managers to understand business requirements and translate them into technical solutions

- Continuously optimize data pipeline performance, reliability, and cost-efficiency using best practices in CI/CD and infrastructure-as-code

- Mentor junior engineers and share your knowledge of data engineering best practices

- Stay up-to-date with the latest big data technologies and architectural patterns, and drive the adoption of innovative solutions

About the team

The Pricing and Promotions Science Data and Insights Org strives to accelerate Customer, Seller, and overall Amazon success through the proactive development of automated intelligent pricing and promotions science and analytics systems. We facilitate making trustworthy data-driven decision making at scale. We look around corners for both long-term and short-term flywheel causal impacts, and think holistically, from sourcing to CX, and all customer journey touch points in between.



Qualifications

- 1+ years of data engineering experience

- Experience with data modeling, warehousing and building ETL pipelines

- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)

- Experience with one or more scripting language (e.g., Python, KornShell)



Extended Qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.



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