Senior Manager of Data Engineering & Business Intelligence, Alexa Audio

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 processes, leveraging AWS technologies and big data tools

• Gather business and functional requirements from product, leadership, and partner teams and translate them into robust, scalable, operable solutions with flexible and adaptable data architecture

• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for stakeholders, Delivery of robust, scalable data solutions supporting Alexa Audio's data infrastructure across all content verticals, endpoints, and geos

• Enhancement of reporting and analytics capabilities serving Alexa Audio Product Directors, Technical Directors, Product Management, Partner Management, and Central BI/Finance teams

• Leadership in data governance, quality standards, and SLA enforcement across the Audio data ecosystem

• Own technical delivery and team leadership for development and maintenance of scalable ETL/big data pipelines, semantic layers, and dashboard data models

• Own and evolve WBR/MBR reporting, self-service analytics, and ad hoc deep-dive capabilities

• Collaborate with Product Management, BI teams, and stakeholders to prioritize work aligned with Alexa Audio business goals

• Establish best practices for data engineering, including code reviews, testing, monitoring, and documentation

• Drive team growth through mentoring, coaching, and career development

• Reduce time-to-insight for product, leadership, and partner teams by increasing data availability and efficiency

• Ensure stakeholders trust the numbers they use to make decisions by improving data confidence and reliability

8+ years of data engineering experience

• Experience with data modeling, warehousing and building ETL pipelines
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• 5+ years of delivering results managing a business intelligence or analytics team, including employee development and performance management experience

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets, or experience with software development lifecycle
• Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience in any Bigdata architecture and experience in managing and troublshooting network
• Experience working directly with business stakeholders to translate between data and business needs

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 202,300.00 - 273,700.00 USD annually

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 of Product Managers, Technical Program Managers, Data Engineers, and Business Intelligence Engineers work together to deliver the data infrastructure, insights, and reporting that power how Alexa Audio understands its business, measures its customer experience, and makes decisions. We are at an inflection point: with the launch of Alexa+, we are delivering smarter, more personalized, and more proactive audio experiences to customers worldwide, and the decisions we make depend on data we can trust, access quickly, and act on confidently.