Data Engineer, Amazon Prime
Role Overview
Amazon Prime Member Experience conducts research and development for Prime, supporting automated marketing, personalization, targeting, and decision systems.
The engineering team builds scalable data infrastructure and products for science and analytics workloads serving Prime members globally.
Key Skills for This Role
Full Job Posting
Role overview
Amazon Prime Member Experience conducts research and development for Prime, supporting automated marketing, personalization, targeting, and decision systems.
The engineering team builds scalable data infrastructure and products for science and analytics workloads serving Prime members globally.
Key responsibilities
- Build and maintain stable, high-performance big data pipelines for machine-learning applications across terabyte-sized datasets.
- Advance data infrastructure with tools such as AWS Glue, Spark, Amazon EMR, and EMR Serverless.
- Implement production data quality monitoring and alerting, including anomaly detection.
- Work with scientists and analysts on data models and analysis-ready datasets.
- Evaluate generative AI tools to automate data workflows and improve productivity.
- Build data solutions with business leaders, scientists, and engineering leaders.
- Use AWS services to process terabyte-scale data and support real-time access and orchestration.
- Take part in code reviews, design discussions, and team planning.
Basic qualifications
- At least 3 years of data engineering experience.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Data engineer or related specialty experience, with a track record of working with large datasets.
Preferred qualifications
- Experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions is preferred.
- Experience with non-relational data stores, such as object, document, key-value, graph, or column-family stores, is preferred.
About the team
The Prime Member Experience engineering team works across large-scale systems, applied science, econometrics, machine learning, and AI.
Data engineers, software engineers, and scientists partner to build and operate real-time science products for customers worldwide.
Compensation
- The posting states that a base salary range is listed below and that total compensation may include sign-on payments and restricted stock units; the provided description does not include the range or its cadence.
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