Amazon.com Services LLC
Technology
SeniorManagerofDataEngineering&BusinessIntelligence
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optimal for Manager candidates.
“Senior Manager of Data Engineering & Business Intelligence at Amazon.com Services LLC. Skills: Data Engineering, Business Intelligence, Data Infrastructure, Data Pipelines. Design and scale data infrastructure. Implement data ingestion routines”
Industry & Context.
Troubleshooting
What They're Looking For.
Must Have
8+ years data engineering experience, Experience with data modeling, Experience building ETL pipelines, Experience in Python, Experience in Java, Experience in Scala, Experience in NodeJS, 5+ years managing BI/analytics team, Employee development experience, Performance management experience
Nice to Have
Experience with AWS technologies, Experience operating distributed systems, Experience with software development lifecycle, Analytical skills, Attention to detail, Effective communication abilities, Big data architecture experience, Managing and troubleshooting network
What You'll Do.
Design and scale data infrastructure
Implement data ingestion routines
Gather business requirements
Translate requirements into solutions
Improve reporting processes
Simplify self-service modeling
Simplify production support
Deliver robust data solutions
Enhance reporting capabilities
Enforce SLA across data ecosystem
Lead development of ETL data pipelines
Lead maintenance of ETL data pipelines
Lead development of semantic layers
Lead maintenance of semantic layers
Lead development of dashboard data models
Lead maintenance of dashboard data models
Evolve WBR/MBR reporting
Evolve self-service analytics
Evolve ad hoc deep-dive capabilities
Collaborate with Product Management
Collaborate with BI teams
Collaborate with stakeholders
Establish best practices
Reduce time-to-insight
Increase data availability
Increase data efficiency
Improve data confidence
Improve data reliability
How You'll Work.
Team & Collaboration
Product teams; Leadership teams; Partner teams; BI teams; Finance teams; Stakeholders
Communication Scope
Effective communication
Full Job Description
Alexa Audio manages the end-to-end customer listening experience for Alexa+ customers worldwide — across all endpoints, in all geos, and for Alexa's global Audio providers including Amazon Music, Apple Music, Spotify, Deezer, and more. Our team ensures that hundreds of millions of customers can discover, play, and enjoy audio content seamlessly through Alexa. Our team of Product Managers, Technical Program Managers, Data Engineers, and Business Intelligence Engineers work together to deliver smarter, more personalized, and more proactive audio experiences. The data that powers our decisions — from listening hours and content performance to quality metrics, discovery, and partner analytics — must be available, efficient, and trusted. As a Sr. Manager of Data Engineering and Business Intelligence, you will lead a team of 6 Data Engineers and BIEs responsible for the data infrastructure, pipelines, and reporting that underpin Alexa Audio's most critical business metrics. You will increase data availability and efficiency, improve data confidence and reliability, and scale existing systems or build net-new infrastructure to support the needs of a rapidly evolving business. You will own end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost- effective. You are passionate about working with large-scale datasets and have experience with the organization and curation of data for analytics. You have a strategic, long-term view on architecting advanced data ecosystems and the ability to integrate data systems with AWS tools and services to support a variety of customer use cases. In this role, you have the opportunity to: - Design and scale the data infrastructure that powers Alexa Audio's key business metrics across all content types (music, radio, podcasts, audiobooks, generative audio), endpoints, geos, and providers - Implement data ingestion routines — both real-time and batch — using best practices in data modeling and ETL/ELT proc
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