ADCI
Business Intelligence, Data Engineering, Voice Technology
DataEngineerII,AlexaEnterpriseData
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer II, Alexa Enterprise Data at ADCI. Skills: Data engineering, Data modeling, ETL pipelines, AWS. Design analytical data infrastructure. Implement analytical data infrastructure”
Industry & Context.
Problem solver; Solving real world problems; Solving challenging data problems; Solving challenging analytic problems
What They're Looking For.
Must Have
3+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with SQL
Nice to Have
Experience with AWS technologies, Experience with non-relational databases
What You'll Do.
Design analytical data infrastructure
Implement analytical data infrastructure
Support analytical data infrastructure
Extract data from sources
Transform data from sources
Load data from sources
Explore AWS technologies
Learn AWS technologies
Collaborate with Data Scientists
Collaborate with Business Intelligence Engineers
Adopt best practices in reporting
Adopt best practices in analysis
Improve reporting processes
Improve analysis processes
Automate self-service support
Simplify self-service support
Maintain internal reporting platforms
Maintain internal reporting tools
Troubleshoot internal reporting platforms
Troubleshoot internal reporting tools
Develop internal reporting platforms
Develop internal reporting tools
Interact with internal users
Establish requirements
Develop report specifications
Shape BI infrastructure development
Implement BI infrastructure development
Contribute to BI tools development
Contribute to BI skills development
Contribute to BI culture development
Contribute to BI impact development
Write advanced SQL queries
Manage data ingestion
Create scalable data models
Use scripting for automation
Use scripting for tool development
Provide infrastructure for self-serve analytics
Provide infrastructure for science use cases
Build CI/CD pipelines
How You'll Work.
Team & Collaboration
Product Managers; Software Engineers; Business Intelligence Engineers; Data Scientists; Engineering partners; UX teams; BDSA teams
Communication Scope
Written communication; Verbal communication
Full Job Description
Amazon is a place where data drives most of our decision-making. Alexa Enterprise team is looking for a dynamic data engineer who can be innovative, a strong problem solver and can lead the implementation of the analytical data infrastructure that will guide decision making. As a Data Engineer, you think like an entrepreneur, constantly innovating and driving positive change, but more importantly, you consistently deliver mind-boggling results. You're a leader, who uses both quantitative and qualitative methods to get things done. And on top of it all, you're someone who wonders "What if?" and then seeks out the solution. This position offers exceptional opportunities to grow your technical and non-technical skills. You have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects. As a Data Engineer, you are responsible for analyzing large amounts of business data, solving real world problems, and developing metrics and business cases that will enable us to continually delight our customers worldwide. This is done by leveraging data from various platforms such as Jira, Portal, Salesforce. You will work with a team of Product Managers, Software Engineers and Business Intelligence Engineers to automate and scale the analysis, and to make the data more actionable to manage business at scale. You will own many large datasets, implement new data pipelines that feed into or from critical data systems at Amazon. You must be able to prioritize and work well in an environment with competing demands. Successful candidates will bring strong technical abilities combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership and a drive to solve some of the most challenging data and analytic problems in retail. Candidates must have demonstrated ability to manage large-scale data modeling
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