Data Engineering Manager, DISCO

Amazon Music is awash in data! To help make sense of it all, the DISCO (Data, Insights, Science & Optimization) team: (i) enables the Consumer Product Tech org make data driven decisions that improve the 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, northstar weblabs metrics to causal frameworks. (ii) delivering exceptional Analytics & Science infrastructure for DISCO teams, fostering a data-driven approach to insights and decision making. As platform builders, we are committed to constructing flexible, reliable, and scalable solutions to empower our customers. (iii) accelerates and facilitates content analytics and provides independence to generate valuable insights in a fast, agile, and accurate way. This domain provides analytical support for the below topics within Amazon Music: Programming / Label Relations / PR / Stations / Livesports / Originals / Case & CAM. DISCO team enables repeatable, easy, in depth analysis of music customer behaviors. We reduce the cost in time and effort of analysis, data set building, model building, and user segmentation. Our goal is to empower all teams at Amazon Music to make data driven decisions and effectively measure their results by providing high quality, high availability data, and democratized data access through self-service tools.

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, and development, deployment, and operations of big data pipelines. Youll help build Amazon Musics most important data pipelines and data sets, and expand self-service data knowledge and capabilities through an Amazon Music data university.
DISCO team develops data specifically for a set of key business domains like personalization and marketing and provides and protects a robust self-service core data experience for all internal customers. We deal in AWS technologies like Redshift, S3, EMR, EC2, DynamoDB, Kinesis Firehose, and Lambda. Your team will manage the data exchange store (Data Lake) and EMR/Spark processing layer using Airflow as orchestrator. Youll build our data university and partner with Product, Marketing, BI, and ML teams to build new behavioural events, pipelines, datasets, models, and reporting to support their initiatives. Youll also continue to develop big data pipelines.

Key job responsibilities
- Lead and mentor a team of data engineers.
- Set team goals, performance metrics, and expectations.
- Foster a collaborative and innovative team culture.
- Recruit, onboard, and retain top talent.
- Oversee the design and implementation of scalable data pipelines.
- Collaborate with cross-functional teams to understand data needs and design solutions.
- Align data solutions with Amazon Musics DISCO architecture goals (cost, security, scalability).
- Manage multiple data engineering projects across DISCO Org.
- Define project timelines, milestones, and deliverables.
- Drive prioritization and trade-off decisions.
- Communicate project progress and risks to DISCO leadership.
- Provide technical guidance to the team on complex data challenges.
- Evaluate new technologies and tools for data infrastructure.
- Lead design and code reviews to maintain high quality standards.
- Monitor and optimize data infrastructure and pipelines for performance and reliability.
- Implement data governance, security, and privacy best practices.
- Establish incident management protocols and ensure effective team response.
- Work with business and product teams to understand data needs.
- Influence decision-making through data-driven insights.
- Communicate effectively with senior leadership on strategy, progress, and challenges.
- Monitor and optimize the cost of data infrastructure and services.
- Manage budget for tools, platforms, and services used by the team.

About the team
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, we are 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 music in shuffle mode, and top ad-free podcasts, included with their membership;customers can upgrade to Music Unlimited for unlimited on-demand access to 100 million songs including millions in HD, Ultra HD, spatial audio and anyone can listen for free by downloading Amazon Music app or via Alexa-enabled devices. Join us for opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. - Bachelors degree in Computer Science, Engineering, Mathematics, or a related field.
- 5+ years of experience in data engineering, software engineering, or related roles.
- 3+ years of experience in leading and managing engineering teams.
- Strong proficiency in data engineering tools and technologies (e. g. , SQL, ETL, data warehousing, distributed systems).
- Experience with cloud platforms (e. g. , AWS, GCP, or Azure) for building scalable data solutions.
- Proficiency in programming languages such as Python, Java or Scala.
- Solid understanding of data architecture, data modeling, and designing large-scale data pipelines.
- Experience with big data technologies (e. g. , Hadoop, Spark, Kafka) and data storage solutions (e. g. , Redshift, Snowflake, S3).
- Ability to manage and prioritize multiple projects and deliver them on time.
- Strong communication skills and the ability to interact with senior leadership and cross-functional teams.