Amazon is hiring: Data Engineer I, Music Finance in Seattle

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 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, development, deployment, and operations of big data pipelines. You'll help build Amazon Music's most important data pipelines and datasets, and expand self-service data knowledge and capabilities through an Amazon Music data university.

Key job responsibilities

1. Deep understanding of data, analytical techniques, and how to connect insights to the business, and practical experience in insisting on the highest standards on operations in ETL and big data pipelines.
2. Assist the DISCO team with management of our existing environment that consists of Redshift and SQL-based pipelines.
3. SQL data pipeline management (creating or updating existing pipelines).
4. Perform maintenance tasks on the Redshift cluster.
5. Assist the team with the management of our next-generation AWS infrastructure. Tasks include infrastructure monitoring via CloudWatch alarms and troubleshooting/root cause analysis of infrastructure issues that arise.

BASIC QUALIFICATIONS

- 2+ years of data engineering experience
- Experience with data modeling, warehousing, and building ETL pipelines
- Experience with SQL
- Experience with one or more scripting languages (e.g., Python, KornShell)
- Experience in Unix
- Experience in troubleshooting issues related to Data and Infrastructure.

PREFERRED QUALIFICATIONS

- 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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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