Alexa is the Amazon cloud service that powers Echo, the groundbreaking new Amazon device designed around your voice. Voice is the most natural user interface for interacting in the home and is quickly becoming the preferred way to seek information on any topic, at any time, from any place. Whether in the kitchen with Echo, on the couch with Fire TV, or on the go with mobile, customers expect Alexa to delight them with immediate and accurate answers to their questions.
The Alexa BI team is looking for an experienced Data Engineer who will be an expert at working with large data sets,will build data pipelines, tools, and reports that enable analysts, knowledge engineers, software engineers, product managers, and executives to improve Alexa’s answering capabilities across multiple information verticals. In this highly visible role, you will work across teams to gather requirements for data logging, storing, transforming, and reporting, and will build salable solutions and UIs that make data accessible and consumable. You enjoy the challenge of highly complex technical contexts, and above all, are passionate about data and analytics.
You love building tools and data pipelines, can create clear and effective reports and data visualizations, and can partner with stakeholders to answer key business questions. Your key responsibilities will be :
· Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources
· Develop and support the analytic technologies that give our teams flexible and structured access to their data, including implementation of a BI platform, defining metrics and KPIs, and automating reporting and data visualization.
· Model data and metadata , build data schema and operate internal data warehouses and SQL/NoSQL database systems for ad hoc and pre-built reporting
· Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, ETL jobs and Spark/Hadoop jobs, python and other scripting languages to calculate business metrics
· Drive architectural plans and implementation for future data storage, reporting, and analytic solutions
· Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
· Monitor and troubleshoot operational or data issues in the data pipelines
· Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
· Meet tight deadlines, multi-task, and prioritize workload