Software Development Engineer, Amazon Music
Amazon.com
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 ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand 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 Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music.
About the team
At Amazon Music, big data is fueling the growth of our business. The Music Privacy & Compliance team is at the fore-front of this growth with platforms and services for facilitating and enabling consumer data privacy. Our team’s mission is to enable Amazon Music teams to proactively respond to consumer privacy laws through large-scale, big data processing workflows. Our systems and workflows focus on building resilient, multi-tenant, secure, and extensible tools and platforms using state of the art technologies. We work on some of the hardest challenges in real time streaming, big data processing, and data analytics on technologies like AWS Kinesis, SQS/SNS, Lambda, Apache Spark, S3, CloudWatch, and various other internal Amazon tools. We are looking for a highly-motivated engineers to help turn Amazon Music’s data into an information advantage. We are a team of rockstars and driven engineers.
If you love the challenges that come with real-time streaming, distributed processing, operational monitoring, timely analysis, and enjoy working with other engineers on data-driven business problems, then this role is for you. You are a talented, enthusiastic, and detail-oriented software developer who wants to work on projects that require innovative thinking, deep technical problem solving, building trust, and mentoring other engineers. You value data-driven decision making and understand that the foundation of good decisions is good data. Most importantly, you are an expert in developing highly scalable and fault-tolerant services and have some experience working with behavioral time series data.
About the team
At Amazon Music, big data is fueling the growth of our business. The Music Privacy & Compliance team is at the fore-front of this growth with platforms and services for facilitating and enabling consumer data privacy. Our team’s mission is to enable Amazon Music teams to proactively respond to consumer privacy laws through large-scale, big data processing workflows. Our systems and workflows focus on building resilient, multi-tenant, secure, and extensible tools and platforms using state of the art technologies. We work on some of the hardest challenges in real time streaming, big data processing, and data analytics on technologies like AWS Kinesis, SQS/SNS, Lambda, Apache Spark, S3, CloudWatch, and various other internal Amazon tools. We are looking for a highly-motivated engineers to help turn Amazon Music’s data into an information advantage. We are a team of rockstars and driven engineers.
If you love the challenges that come with real-time streaming, distributed processing, operational monitoring, timely analysis, and enjoy working with other engineers on data-driven business problems, then this role is for you. You are a talented, enthusiastic, and detail-oriented software developer who wants to work on projects that require innovative thinking, deep technical problem solving, building trust, and mentoring other engineers. You value data-driven decision making and understand that the foundation of good decisions is good data. Most importantly, you are an expert in developing highly scalable and fault-tolerant services and have some experience working with behavioral time series data.
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