Amazon Music is awash in data!
To help make sense of it all, the DISCO (Data, Insights, Science & Optimization) team enables the Consumer Product Tech org to make data-driven decisions that improve 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 to causal frameworks.
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 a 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.
Key job responsibilitiesDeep understanding of data, analytical techniques, and how to connect insights to the business, with practical experience insisting on the highest standards in operations in ETL and big data pipelines.Assist the DISCO team with management of our existing environment that consists of Redshift and SQL-based pipelines, including approving data access requests and adding new data.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, including monitoring via CloudWatch and troubleshooting infrastructure issues.BASIC QUALIFICATIONS2+ years of data engineering experienceExperience with data modeling, warehousing, and building ETL pipelinesExperience with SQLExperience with one or more scripting languages (e.g., Python, KornShell)Experience in UnixExperience in troubleshooting issues related to data and infrastructurePREFERRED QUALIFICATIONSExperience with big data technologies such as Hadoop, Hive, Spark, EMRExperience with ETL tools like Informatica, ODI, SSIS, BODI, DatastageKnowledge of distributed systems as it pertains to data storage and computingExperience in building or administering reporting/analytics platformsOur inclusive culture empowers Amazonians to deliver the best results for our customers.
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