Data Engineering Manager, Amazon Music Technology

We are seeking an ambitious Data Engineering Manager to join our Metrics and Data Platform team. The Metrics and Data Platform team plays a critical role in enabling Amazon Musics business decisions and datadriven software development by collecting and providing behavioral and operational metrics to our internal teams. We maintain a scalable and robust data platform to support Amazon Musics rapid growth and collaborate closely with data producers and data consumers to accelerate innovation using data.

As a Data Engineering Manager you will manage a team of talented Data Engineers. Your team collects billions of events a day manages petabytescale datasets on Redshift and S3 and develops data pipelines with Spark SQL EMR and Airflow. You will collaborate with product and technical stakeholders to solve challenging data modeling data availability data quality and data governance problems.

At Amazon Music engineering managers are the primary drivers of their teams roadmap priorities and goals. You will be deeply involved in your teams execution helping to remove obstacles and accelerate progress. A successful candidate will be customer obsessed highly analytical and detail oriented able to work effectively in a dataheavy organization and adept at leading across multiple different complex workstreams at once.

Key job responsibilities
Hiring motivating mentoring and growing a highperforming engineering team
Owning and managing big data pipelines Amazon Musics foundational datasets and the quality and operational performance of the datasets
Collaborating with crossfunctional teams and customers including business analysts marketing product managers technical program managers and software engineers/managers
Defining and managing your teams roadmap priorities and goals in partnership with Product stakeholders and leaders
Ensuring timely execution of team priorities and goals by proactively identifying risks and removing blockers
Recognizing and recommending process and engineering improvements that reduce failures and improve efficiency
Clearly communicating business updates verbally and in writing to both technical and nontechnical stakeholders peers and leadership
Effectively influencing other teams priorities and managing escalations
Owning and improving business and operational metrics of your teams software
Ensuring team compliance with policies (e.g. information security data handling service level agreements)
Identifying ways to leverage GenAI to reduce operational overhead and improve execution velocity
Introducing ideas to evolve and modernize our data model to address customer pain points and improve query performance

About the team
Amazon Music is an immersive audio entertainment service that deepens connections between fans artists and creators. From personalized music playlists to exclusive podcasts concert livestreams to artist merch Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode and top adfree podcasts included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited ondemand access to 100 million songs including millions in HD Ultra HD and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexaenabled devices. Join us for the opportunity to influence how Amazon Music engages fans artists and creators on a global scale. Learn more at 5 years of data engineering experience
Experience with data modeling warehousing and building ETL pipelines
Experience with SQL
Experience managing a data or BI team
Experience leading and influencing the data or BI strategy of your team or organization
Experience in at least one modern scripting or programming language such as Python Java Scala or NodeJS
Experience with big data technologies such as: Hadoop Hive Spark EMR
Experience hiring developing and promoting engineering talent
Experience communicating to senior management and customers verbally and in writing

Experience with AWS Tools and Technologies (Redshift S3 EC2)
Experience in processing data with a massively parallel technology (such as Redshift Teradata Netezza Spark or Hadoop based big data solution)

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