Data Engineer, PXT Central Science

Responsibilities

• Data Pipeline Development: Design and maintain scalable data pipelines using native AWS services (Glue, EMR, Lambda); build monitoring and error handling for data workflows; optimize performance, reliability, and cost efficiency
• Model Productionization & API Development: Develop and maintain APIs and data serving layers that productionize science models for downstream consumption; build batch and real-time inference pipelines
• Data Integration & Quality: Build scalable feature extraction and processing frameworks for diverse data types; develop robust data quality and validation checks; create flexible schemas supporting evolving requirements
• Cross-team Collaboration: Partner with economics, data science, and software engineering teams to translate analytical requirements into production-ready solutions; participate in technical design reviews and architecture discussions
• Analytics & Infrastructure: Maintain layered data systems used by economists and scientists; build automated reporting solutions; work across multiple interconnected AWS accounts with security best practices

About the Team

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science, engineering, and UX to develop and deliver solutions that measurably achieve this goal.

Qualifications

• 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
• 3+ years of data engineering experience
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience with data modeling, warehousing and building ETL pipelines
• 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)