Job description

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. Learn more at amazon.com. 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. Key job responsibilities • Partner with cross-functional teams — data scientists and Finance managers — to architect a modern data analytics platform on AWS using the Cloud Development Kit (CDK). • Build resilient, scalable data pipelines with SQL, PySpark, and Airflow to ingest, process, and transform large data volumes from diverse sources into structured, high-quality datasets. • Design and implement a scalable data warehousing solution on AWS, using the appropriate NoSQL and SQL storage and database technologies for structured and unstructured data. • Build a consolidated data model that serves as the single source of truth, so metric logic is defined and changed once rather than patched across disconnected jobs. • Automate ETL and ELT processes to streamline data integration across sources and improve platform reliability and efficiency. • Own the business intelligence layer end to end: build the data models, metrics, dashboards, and interactive reports that deliver actionable insights to Finance managers and other end users. • Build AI and generative AI infrastructure that automates recurring Finance reporting and process work, using tools such as EMR and SageMaker to extract predictive and prescriptive insights. • Build AI agents and agentic infrastructure that let Finance managers self-serve their questions and analytics, reducing ad hoc reporting requests. • Build KPI and ETL job-monitoring systems with freshness SLAs, anomaly detection, and lineage tracking, so business-critical reports arrive on time and data access stays low-latency for analytics and machine learning. • Partner with the central infrastructure team to drive infrastructure enhancements for Finance-specific use cases. • Implement robust security measures and ensure data compliance with internal requirements, industry standards, and regulations to protect sensitive information. • Work closely with data scientists and Finance managers to understand their reporting and analytics requirements and translate them into platform capabilities. • Produce clear technical documentation covering the platform's architecture, data models, and APIs to support knowledge sharing and maintainability. - 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) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 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 amazon.jobs for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at amazon.jobs . USA, CA, Culver City - 132,100.00 - 178,800.00 USD annually USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually

Requirements

Must-haves

Key job responsibilities
Partner with cross-functional teams — data scientists and Finance managers — to architect a modern data analytics platform on AWS using the Cloud Development Kit (CDK).
Build resilient, scalable data pipelines with SQL, PySpark, and Airflow to ingest, process, and transform large data volumes from diverse sources into structured, high-quality datasets.
Design and implement a scalable data warehousing solution on AWS, using the appropriate NoSQL and SQL storage and database technologies for structured and unstructured data.
Build a consolidated data model that serves as the single source of truth, so metric logic is defined and changed once rather than patched across disconnected jobs.
Automate ETL and ELT processes to streamline data integration across sources and improve platform reliability and efficiency.
Own the business intelligence layer end to end: build the data models, metrics, dashboards, and interactive reports that deliver actionable insights to Finance managers and other end users.
Build AI and generative AI infrastructure that automates recurring Finance reporting and process work, using tools such as EMR and SageMaker to extract predictive and prescriptive insights.
Build AI agents and agentic infrastructure that let Finance managers self-serve their questions and analytics, reducing ad hoc reporting requests.
Build KPI and ETL job-monitoring systems with freshness SLAs, anomaly detection, and lineage tracking, so business-critical reports arrive on time and data access stays low-latency for analytics and machine learning.
Partner with the central infrastructure team to drive infrastructure enhancements for Finance-specific use cases.
Implement robust security measures and ensure data compliance with internal requirements, industry standards, and regulations to protect sensitive information.
Work closely with data scientists and Finance managers to understand their reporting and analytics requirements and translate them into platform capabilities.
Produce clear technical documentation covering the platform's architecture, data models, and APIs to support knowledge sharing and maintainability.
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)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, CA, Culver City - 132,100.00 - 178,800.00 USD annually
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually

Nice-to-haves

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Application prep

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Keywords to mirror

awssqlaimachine learning

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave