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# Data Engineer, Amazon Music, Amazon Music Finance

- **Company:** Amazon.com, Inc.
- **Location:** Seattle, WA, United States
- **Experience:** Experienced
- **Salary:** $132,100.0 - $178,800.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Business Analytics Applications, Data Analysis, Databases, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Security, Data Stores, Data Warehousing, Graph Database, Identity and Access Management, Machine Learning, NoSQL, SQL Databases, Unstructured Data, Electronic Medical Records, Generative AI, Pyspark, AWS Glue, Data Analytics, Non-relational Database, Data Pipelines, Amazon Redshift
- **Published:** September 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6539144f205c5e44

## About the Role

* 3+ years of data engineering experience
 * Experience with data modeling, warehousing and building ETL pipelines
 * Bachelor's degree, * Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
 * Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

## Description

The Data, Insights, Science and Optimization, Finance (DISCO Finance) team is looking for a Data Engineer to join a team of Data Scientists, Business Intelligence Engineers, and Data Engineers who analyze data at scale and build the models and algorithms that power the Music product experience. DISCO Finance accelerates Amazon Music customer growth by empowering Product teams to make customer-centric decisions through data and insights. We build the data pipelines, self-service analytics, and predictive models that enable acquisition, engagement, and retention at scale.

In this role, you will design, build, and own the data infrastructure and pipelines that power the team's analytics and science, and partner with stakeholders across marketing, growth, product, science, and finance to scale those capabilities. The ideal candidate builds reliable large-scale data solutions, prioritizes across competing stakeholders and projects, and thrives in a fast-paced, dynamic environment., * Engage in collaborative efforts with cross-functional teams - data scientists, business intelligence engineers, and Finance Managers - to architect a state-of-the-art data analytics platform on AWS using the AWS Cloud Development Kit (CDK).

 * Construct resilient and scalable data pipelines using SQL/PySpark/Airflow to ingest, process, and transform substantial data volumes from diverse sources into a structured format, ensuring data quality and integrity.
 * Devise and implement an efficient, scalable data warehousing solution on AWS, utilizing appropriate NoSQL/SQL storage and database technologies for both structured and unstructured data.
 * Automate ETL/ELT processes to streamline data integration from diverse sources, enhancing the platform's reliability and efficiency.
 * Develop data models to support business intelligence, delivering actionable insights and interactive reports to end-users.
 * Enable advanced analytics, machine learning, and generative AI capabilities within the platform, extracting predictive and prescriptive insights through tools like EMR and SageMaker.
 * Continuously monitor and optimize the performance of data pipelines, databases, and applications, ensuring low-latency data access for analytics and machine learning tasks.
 * Implement robust security measures and ensure data compliance with internal requirements, industry standards, and regulations to safeguard sensitive information.
 * Collaborate closely with data scientists, business intelligence engineers, and Finance Managers to understand their requirements and partner on data projects.
 * Generate comprehensive technical documentation covering the platform's architecture, data models, and APIs, promoting knowledge sharing and ease of maintainability.