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.
We are seeking an ambitious Data Engineer to join our Metrics and Data Platform team. The Metrics and Data Platform team plays a critical role in enabling Amazon Music’s business decisions and data-driven 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 Music’s rapid growth, and collaborate closely with data producers and data consumers to accelerate innovation using data.
As a Data Engineer, you will drive engineering and operational projects for the Metrics and Data Platform team. You will work with Product to understand top customer pain points and with our data engineering team to understand desired operational improvements. You will implement and own operational improvements and solutions as well as enhancements to key business datasets. You will model and build extensible and intuitive datasets for over 50 unique internal customers. Your datasets will directly inform leadership questions on customer engagement, determine external payments to music labels, and help drive product improvements to search, personalization, and more.
You are a talented, enthusiastic, and detail-oriented data engineer who wants to work on projects that require innovative thinking and deep technical problem solving. You have strong SQL skills and are familiar with common data modeling concepts. You value data-driven decision making and understand that the foundation of good decisions is good data. You write clear, professional documents accessible to both technical staff and stakeholders. You enjoy engaging in passionate discussions with smart people and letting the best ideas rise to the top. You see your mistakes as learning opportunities and continually look for ways to improve yourself, your team, and your products. You are a quick and willing learner of new technologies.
Key job responsibilities
* Writing high quality code/SQL and reviewing code/SQL across the team
* Ensuring timely delivery of assigned projects by proactively identifying risks and removing blockers
* Ability to dive deep, diagnose, and root cause bugs, bottlenecks, or inefficiencies
* Collaborating with product managers and software engineers/managers
* Clearly communicating project updates, verbally and in writing, to both technical and non-technical stakeholders and peers
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
- Experience with SQL
- Strong written and verbal communication skills
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with at least one modern language such as Java, Python, C++, or C# including object-oriented design
- Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
- Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
- 2+ years of experience as a Data Engineer or in a similar role
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