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Data Engineering Manager, Disco

1 week ago


Dublin, Dublin City, Ireland Amazon Full time

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 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.
You'll help build Amazon Music's 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.
You'll build our data university and partner with Product, Marketing, BI, and ML teams to build new behavioral events, pipelines, datasets, models, and reporting to support their initiatives.
You'll also continue to develop big data pipelines.
Key job responsibilitiesLead 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 Music's 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.BASIC QUALIFICATIONSBachelor's 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.PREFERRED QUALIFICATIONSExperience with machine learning pipelines and integrating machine learning models into data workflows.Expertise in data governance, security, and privacy practices.Familiarity with agile methodologies and using tools like Jira or Confluence.Proven track record of driving technical strategy and influencing stakeholders across the organization.Strong problem-solving and analytical skills with a passion for technical innovation.Experience with data visualization tools (e.g., Tableau, Looker) or business intelligence tools.Familiarity with automation and DevOps practices in the data engineering space.Certifications related to cloud technologies (e.g., AWS Certified Solutions Architect, Google Cloud Professional Data Engineer).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 this link for more information.
If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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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