Description

Analytics Delivery Services (ADS) is a centralized technology, data, reporting, and analytics organization that supports over a million employees globally, spanning support across NA Customer Fulfillment, Global Operations Learning & Development and PXT Capability & Impact, and Employee Relations (ER).

We are looking for a skilled Data Engineer to build and optimize scalable data solutions that support our mission of securely managing, distributing, and storing ER data. This team plays a critical role in defining the data strategy for Employee Relations by architecting and maintaining data infrastructure that enables accurate and efficient data access for downstream applications and teams. The ideal candidate will collaborate with cross-functional teams, including Data Scientists, Business Intelligence Engineers (BIE), and Software Development Engineers, to deliver impactful data solutions.

As a Data Engineer, you will analyze large amounts of business data, solve real world problems, and develop metrics and business cases that will enable us to continually deliver on people metrics. You will monitor and improve data infrastructure performance, troubleshooting bottlenecks and implementing optimizations as needed to make the data more actionable to manage business at scale. You will own many large datasets, production pipelines, automate anomaly detection model, data models, implement new data pipelines that feed into or from critical data systems at Amazon


Key job responsibilities
• Work closely with senior engineers to model, implement data pipelines that feed into or from people data across middle and last mile.
• Own the delivery of data modelling and data pipelines.
• Management and execution against project plans and delivery commitments
• Assist directly and indirectly in the continual hiring and development of technical talent.
• Create and execute appropriate quality plans, project plans, test strategies and processes for development activities in concert with business and project management efforts.
• Maintain in-house cluster and continuously work on improving cluster health with enabling alerts and key functions