Amazon Music is awash in data! To help make sense of it all, the DISCO (Data, Insights, Science & Optimization) team: (i) enables the Consumer Product Tech org make data driven decisions that improve the customer retention, engagement and experience on Amazon Music. We build and maintain automated self-service data solutions, data science models and deep dive difficult questions that provide actionable insights. We also enable measurement, personalization and experimentation by operating key data programs ranging from attribution pipelines, northstar weblabs metrics to causal frameworks. (ii) delivering exceptional Analytics & Science infrastructure for DISCO teams, fostering a data-driven approach to insights and decision making. As platform builders, we are committed to constructing flexible, reliable, and scalable solutions to empower our customers. (iii) accelerates and facilitates content analytics and provides independence to generate valuable insights in a fast, agile, and accurate way. This domain provides analytical support for the below topics within Amazon Music: Programming / Label Relations / PR / Stations / Livesports / Originals / Case & CAM. DISCO team enables repeatable, easy, in depth analysis of music customer behaviors. We reduce the cost in time and effort of analysis, data set building, model building, and user segmentation. Our goal is to empower all teams at Amazon Music to make data driven decisions and effectively measure their results by providing high quality, high availability data, and democratized data access through self-service tools.
If you love the challenges that come with big data then this role is for you. We collect billions of events a day, manage petabyte scale data on Redshift and S3, and develop data pipelines using Spark/Scala EMR, SQL based ETL, Airflow and Java services.
We are looking for talented, enthusiastic, and detail-oriented Data Engineer, who knows how to take on big data challenges in an agile way. Duties include big data design and analysis, data modeling, and development, deployment, and operations of big data pipelines. You'll help build Amazon Music's most important data pipelines and data sets, and expand self-service data knowledge and capabilities through an Amazon Music data university.
DISCO team develops data specifically for a set of key business domains like personalization and marketing and provides and protects a robust self-service core data experience for all internal customers. We deal in AWS technologies like Redshift, S3, EMR, EC2, DynamoDB, Kinesis Firehose, and Lambda. Your team will manage the data exchange store (Data Lake) and EMR/Spark processing layer using Airflow as orchestrator. You'll build our data university and partner with Product, Marketing, BI, and ML teams to build new behavioural events, pipelines, datasets, models, and reporting to support their initiatives. You'll also continue to develop big data pipelines.
Key job responsibilities
• Deep understanding of data, analytical techniques, and how to connect insights to the business, and you have practical experience in insisting on highest standards on operations in ETL and big data pipelines. With our Amazon Music Unlimited and Prime Music services, and our top music provider spot on the Alexa platform, providing high quality, high availability data to our internal customers is critical to our customer experiences.
• Assist the DISCO team with management of our existing environment that consists of Redshift and SQL based pipelines. The activities around these systems will be well defined via standard operation procedures (SOP) and typically involve approving data access requests, subscribing or adding new data to the environment
• SQL data pipeline management (creating or updating existing pipelines)
• Perform maintenance tasks on the Redshift cluster.
• Assist the team with the management of our next-generation AWS infrastructure. Tasks includes infrastructure monitoring via CloudWatch alarms, infrastructure maintenance through code changes or enhancements, and troubleshooting/root cause analysis infrastructure issues that arise, and in some cases this resource may also be asked to submit code changes based on infrastructure issues that arise.
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,we are 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 music in shuffle mode,and top ad-free podcasts,included with their membership;customers can upgrade to Music Unlimited for unlimited on-demand access to 100 million songs including millions in HD,Ultra HD,spatial audio and anyone can listen for free by downloading Amazon Music app or via Alexa-enabled devices.Join us for opportunity to influence how Amazon Music engages fans, artists,and creators on a global scale.
- 2+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience with one or more scripting language (e.g., Python, KornShell)
- Experience in Unix
- Experience in Troubleshooting the issues related to Data and Infrastructure issues.
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience in building or administering reporting/analytics platforms