Description

Amazon's Under The Roof Data Engineering team supports workforce planning operations across 2200+ sites in North America and Europe, managing data infrastructure for Amazon's most innovative business lines. We are recruiting a data engineer to join our team as we build next-generation labor planning solutions that combine robust data infrastructure with intelligent automation. You will get the opportunity to work collaboratively with a variety of stakeholders, including Software Engineers, Applied Scientists, Data Scientists, and our customers while contributing to next-generation initiatives including AI-powered labor planning agents, modern data lake architectures, and self-service experimentation platforms that are reshaping how Amazon approaches workforce optimization.

The ideal candidate will demonstrate strong data engineering skills and show curiosity to understand the business context of their work. You will have the opportunity to work on innovative AI projects including natural language processing agents for labor planning inputs, knowledge graph implementations for enhanced data discovery, and LLM-powered automation tools. The candidate will have attention to detail, be proficient in SQL/DWH/Python and solve data and reporting challenges with guidance from senior team members. The role requires good communication skills and the ability to work effectively with other functional teams in a fast-paced innovation environment.


Key job responsibilities
* Contribute to the development of AI-powered labor planning solutions, including conversational agents that enable natural language interaction with planning data and LLM-driven incident response automation.
* Support the implementation of knowledge graph platforms using AWS Neptune and declarative metrics engines that power next-generation analytics applications.
* Participate in the migration of our data lake to Apache Iceberg format, implementing modern table formats that enable sub-minute metric latency and enhanced query performance for AI workloads.
* Work with next-generation AWS services including ECS, EMR, S3, Glue, Redshift, and emerging AI services like Bedrock to build scalable data solutions that support both traditional analytics and intelligent applications.
* Collaborate on the development of self-service experimentation platforms, enabling science and guidance teams to independently test and deploy machine learning models with automated data integration.
* Contribute to AI-driven data augmentation capabilities, implementing intelligent data imputation techniques and synthetic data generation that extends planning horizons from 26 to 52 weeks.
* Support near real-time data domain implementations for core labor planning inputs including roster, attendance, and attrition data, sourced directly from systems of record.
* Interface with technology teams to build robust data pipelines that support both human decision-making and AI agent interactions, ensuring data quality through automated validation and monitoring.
* Learn and adopt the latest AWS AI/ML technologies and open-source semantic layer frameworks to provide new capabilities that bridge traditional data engineering with modern intelligent architectures.
* Collaborate with and support Business Intelligence Engineers and AI/ML teams by implementing best practices in data infrastructure that enables both reporting workflows and conversational analytics experiences.
* Work with stakeholders to understand evolving business questions in an AI-enhanced environment and implement scalable data solutions that support both traditional planning tools and innovative agent-based interfaces.
* Support and improve ongoing processes through automation, contributing to reducing manual touch points by 50% while enabling intelligent, context-aware decision support systems.