AmazonData Engineer, Amazon Prime
Amazon is hiring a Data Engineer, Amazon Prime in Seattle, United States. It pays $132k-$179k a year and Level rates it ; you can apply on Level.
AI in this role
Build big data pipelines and scalable infrastructure to support machine learning and personalization for Amazon Prime.
As Prime expands its science-driven capabilities globally, we are growing the engineering team to meet increasing demand for reliable, high-throughput data infrastructure. Do you want to work with Amazon's best engineers on hard problems at massive scale? Do you want to impact over 300 million Prime members worldwide? Are you someone who likes using big data to drive high-impact business decisions? If so, come join our team!
Key job responsibilities
Build and maintain big data pipelines for machine learning applications at Amazon scale, ensuring stability and performance across terabyte-sized datasets
Advance data engineering infrastructure using tools such as AWS Glue, Spark, Amazon EMR, and EMR Serverless to support science and analytics workloads
Design and implement proactive data quality monitoring and alerting (e.g., anomaly detection) across production pipelines to safeguard downstream models
Collaborate with scientists and analysts to create coherent data models and analysis-ready datasets that improve the customer experience for over 300 million members worldwide
Evaluate and integrate generative AI tools where appropriate to automate data workflows and improve team productivity
A day in the life
You will collaborate closely with Prime business leaders, scientists (economists, research scientists, applied scientists), and engineering leaders to build data solutions. You will work with AWS technologies such as Amazon EMR, Amazon S3, AWS Glue, AWS Lambda, and Amazon DynamoDB to process terabyte-scale data and support real-time access and orchestration across multiple systems. Your work will directly enhance scientific models and data applications that shape the Prime member experience globally. You will also participate in code reviews, design discussions, and team planning alongside both technical and business stakeholders.
About the team
The Prime Member Experience engineering team sits at the intersection of large-scale engineering systems and applied science ,econometrics, machine learning, and AI delivering applications that reach over 300 million customers. Our team includes data engineers, software engineers, and scientists who partner closely to build and operate real-time science products. We are focused on enabling Prime Science adoption worldwide across Amazon, and the growing complexity of our real-time data products creates data engineering challenges that give you hands-on experience with problems the broader industry will face in the years ahead.
Basic qualifications
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
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)
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
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, Amazon Prime at Amazon rates 60 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.
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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- This job starts at
- $132k
- Typical data engineer job
- $150k
This posting starts 12% below the typical data engineer job. See data engineer jobs
Questions you could be asked
- Tell me about a project where big data was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where machine learning infrastructure was part of your work. What did you do?
- Tell me about a project where data quality was part of your work. What did you do?
- Tell me about a project where anomaly detection was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Big Data, Data Pipelines, Machine Learning Infrastructure, Data Quality, and Anomaly Detection. 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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