Data Engineer, Time and Pay Innovation

Are you passionate about data and code? Does the prospect of dealing with massive volumes of data excite you? Do you want to build data engineering solutions that process billions of records and support handling of HR transactions data using AWS technologies?

Amazon is one of the largest employers on the planet with hundreds of thousands of employees across the globe. Amazon's HR mission is to build a workplace for Amazonians to invent on behalf of our customers. The volume of internal human resource transactions and range of experiences to fulfill at this scale are massive and unique. This requires highly reliable, scalable and customized software applications that ensure our global employee base receives accurate, timely and best experiences throughout their employee lifecycle.

Our Time and Attendance group is seeking a bright and motivated Data Engineer for leading the launch of timekeeping systems to support business expansions and deliver automations to achieve process efficiency and perfect pay for associates. As a Data Engineer, you would own the architecture of Data Warehouse solutions using multiple platforms. You would have the opportunity to lead the design, creation and management of extremely large datasets working backwards from business use cases. You will use your strong business and communication skills to work with business analysts and engineers to determine how best to design the data warehouse for reporting and analytics. You will be responsible for designing and implementing scalable ETL processes to support the rapidly growing and dynamic business demand for data, and use it to deliver data as a service which will have an immediate influence on day-to-day decision making.

Key Job Responsibilities

• Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal tools (Datanet, Cradle, QuickSight etc.).
• Build integrations between HR, Time & Attendance and Payroll systems to automate employee hire, schedule, punch and pay.
• Develop new data models and end-to-end data pipelines.
• Improve existing solutions and architect next-generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.
• Translate business and functional requirements into robust, scalable, operable solutions that work well within the overall data architecture.
• Design, develop, implement, test, document, and operate large-scale, high-volume and low latency applications.
• Design data integrations and data quality framework.