Data Engineer I, Music Finance

Amazon; London; On-site; GBP 50,000 - 90,000; Full time

Job summary

Join a dynamic team at a leading audio entertainment service, where you will tackle big data challenges and contribute to building scalable data solutions. As a Data Engineer, you will work with cutting-edge technologies to enhance customer experiences through data-driven insights. Your role will involve developing and maintaining data pipelines, collaborating with cross-functional teams, and ensuring high-quality data availability. This is an exciting opportunity to influence how music connects with fans globally, all while working in a supportive and innovative environment. If you're passionate about data and technology, this role is perfect for you!

Qualifications

• 2+ years of data engineering experience with a strong focus on ETL pipelines.
• Experience in SQL and one or more scripting languages such as Python.

Responsibilities

• Design and maintain data pipelines for Amazon Music using AWS technologies.
• Assist in managing Redshift and SQL-based data environments.

Skills

Data Engineering

SQL

Python

Data Modeling

ETL Pipelines

Unix

Troubleshooting

Education

Bachelor's Degree in Computer Science or related field

Tools

Redshift

Spark

Airflow

AWS

Hadoop

Informatica

Job description

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About Amazon Music & the DISCO Team

Amazon Music handles vast amounts of data. The DISCO (Data, Insights, Science & Optimization) team enables the Consumer Product Tech organization to make data-driven decisions that enhance customer retention, engagement, and experience on Amazon Music. We develop and maintain automated data solutions, data science models, and conduct deep dives into complex questions to produce actionable insights. Our work supports measurement, personalization, and experimentation through key data programs, including attribution pipelines, web metrics, and causal frameworks.

We provide analytics and science infrastructure, fostering a data-driven culture with scalable, reliable solutions. Our team accelerates content analytics, offering independence for generating insights quickly and accurately. We support various domains within Amazon Music, such as Programming, Label Relations, PR, Stations, Livesports, Originals, and Case & CAM, enabling repeatable analysis of music customer behaviors and reducing analysis costs.

Role Overview

If you love big data challenges, this role is for you. You will work with billions of events daily, managing petabyte-scale data on Redshift and S3, and develop data pipelines using Spark/Scala EMR, SQL ETL, Airflow, and Java services.

We seek a talented, enthusiastic, and detail-oriented Data Engineer to design, analyze, model, and operate big data pipelines. You will help build Amazon Music's key data pipelines and expand our self-service data capabilities through our data university.

Key Responsibilities

1. Deep understanding of data and analytical techniques, connecting insights to business needs, and maintaining high standards in ETL and data pipelines.
2. Manage existing Redshift and SQL-based environments, including data access approvals and data management activities.
3. Develop and update SQL data pipelines.
4. Perform maintenance on Redshift clusters.
5. Assist with managing AWS infrastructure, including monitoring, troubleshooting, and code enhancements.
6. Build and develop data pipelines, datasets, models, and reporting tools in collaboration with various teams.

About the Team

Amazon Music offers immersive audio experiences, connecting fans, artists, and creators through personalized playlists, podcasts, livestreams, and merchandise. We serve diverse customer needs with different tiers of service, including Prime, Music Unlimited, and free listening options. Join us to influence how Amazon Music engages a global audience.

Basic Qualifications

• 2+ years of data engineering experience
• Experience with data modeling, warehousing, and ETL pipelines
• Proficiency in SQL
• Experience with scripting languages like Python or KornShell
• Unix experience
• Troubleshooting data and infrastructure issues

Preferred Qualifications

• Experience with Hadoop, Hive, Spark, EMR
• Experience with ETL tools like Informatica, ODI, SSIS, BODI, DataStage
• Knowledge of distributed storage and computing systems
• Experience with reporting and analytics platforms

We promote an inclusive culture and provide accommodations for applicants with disabilities. For more information, visit this link.