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Amazon.com Posted 4 months ago

Interested in Amazon Alexa Automotive? You can be part of the team that makes Alexa Automotive available across the globe.





You will have an enormous opportunity to build and influence the data sets that drive customer experience, design and implementation of cutting-edge Alexa Automotive solutions that will be used every day by people you know. We’re looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of ownership and want to have fun while they make history.





Amazon is seeking an experienced Data Engineer who is looking to work in a new space to help define how we use data to understand customer behavior and satisfaction. In this role, you will develop and support the analytic technologies that give our teams’ flexible and structured access to their data, including building upon our BI platform with new pipelines and dataset, defining metrics and KPIs, and automating.





Responsibilities

· You know and love working with business intelligence tools, can model multidimensional datasets, and can partner with customers to answer key business questions. You will also have the opportunity to display your skills in the following areas:

· Consult with Product, Marketing, and Finance teams to identify data need to analyze key business decisions.

· Own the development and maintenance of operational reports for weekly, monthly, annual business reviews.

· Interface directly with the customer to determine core data report needs, process improvement and roadmaps moving forward.

· Own the implementation of self-service analytics capabilities for stakeholders. (e.g. Tableau dashboards)

· Ad hoc analysis of developer and customer engagement

· Collaborate with Data Engineers and Software Engineers to implement the data architecture and design.



Basic Qualifications

· 3+ years of experience as a Data Engineer or in a similar role

· Experience with data modeling, data warehousing, and building ETL pipelines

· Experience in SQL

· Bachelor’s degree in Computer Science, Mathematics, Statistics, Finance, related technical field, or equivalent work experience.

· 3-5 years of years of relevant work experience in analytics, data engineering, business intelligence, market research or related field, and 7-10 years professional experience (experience in consumer-facing industry preferred)

· Experience gathering business requirements, using industry standard business intelligence tool(s) to extract data, formulate metrics and build reports

· Experience using SQL, ETL and databases in a business environment with large-scale, complex datasets







Preferred Qualifications · 4+ years of professional experience as a Data Engineer

· Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for Business Intelligence analytics.

· Gather business and functional requirements and translate them into robust, scaleable, operable solutions that work well within the overall data architecture.

· Implement data structures using best practices in data modeling, ETL/ELT process and SQL.

· Provide on-line reporting and analysis using Business Intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources.

· Analyze source data systems and drive best practices in source teams.

· Use full life practices from design, implementation and testing, to documentation, delivery, support and maintenance.

· Produce comprehensive, usable dataset documentation and metadata.

· Data Warehousing Experience with Oracle, Redshift, Teradata, etc.

· Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)

· Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc)

· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

· Evaluate and make decisions around dataset implementations and the use of new or existing software products and tools.