Description de l'offre
Alexa is Amazon's groundbreaking virtual assistant designed for voice interactions. We believe voice is the most natural interface for interacting with technology across many domains. We are looking for a Data Engineer to join our Analytics team located in beautiful Santa Barbara, CA.
As a Data Engineer, you will build data pipelines, tools, and reports that enable analysts, knowledge engineers, software engineers, product managers, and executives improve Alexa's answering capabilities across multiple information verticals: Sports, Business, History, Science, etc. In this highly visible role, you will work across teams to gather requirements for data logging, storing, transforming, and reporting, and will build scalable solutions under fast-paced environment.
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. You will also have the opportunity to display your skills in the following areas:
· Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources
· Design data schema and operate internal data warehouses and SQL/NoSQL database systems
· Write Extract-Transform-Load (ETL) jobs and Spark/Hadoop jobs to calculate business metrics
· 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
· Drive architectural plans and implementation for future data storage, reporting, and analytic solutions
· Bachelor's degree in Computer Science, Mathematics, Statistics, Finance, related technical field, or equivalent work experience
· 3+ years of relevant work experience in analytics, data engineering, business intelligence or related field, and 3+ years professional experience
· 2+ years of experience in implementing big data processing technology: Hadoop, Apache Spark, etc.
· Experience using SQL queries, experience in writing and optimizing SQL queries in a business environment with large-scale, complex datasets
· Detailed knowledge of data warehouse technical architecture, infrastructure components, ETL and reporting/analytic tools and environments
· Experience in data visualization software (Tableau/Qlikview) or open-source project