Data Engineer - Music DISCO, Music DISCO
Amazon is hiring a Data Engineer - Music DISCO, Music DISCO in Mexico City, Mexico. Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
- The posting mentions SageMaker, Spark and Scala among its tools and skills.
- Level classes it as a mid-level role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Build and maintain petabyte-scale big data pipelines and infrastructure to support music analytics, personalization, and experimentation.
This domain provides analytical support for the Consumer Product Tech org to make data driven decisions while launching new features and evaluating existing features with the end goal of improving the customer experience.
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 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 behavioural events, pipelines, datasets, models, and reporting to support their initiatives. You'll also continue to develop big data pipelines.
Key job responsibilities
You will work with Product Managers, Data scientists and other Data Engineers to help design, develop and deliver scalable data analytics platform and data pipeline solutions to support various Science, ML initiatives and at the scale and speed of Amazon Music. In addition, you will help design, develop, and deliver components for the analytics platform at the broader org level and streamline/automate workflows for the broader DISCO organization.
A day in the life
-Collaborate with cross-functional teams, including data scientists, data scientists, business intelligence engineers, to design and architect a modern data analytics platform on AWS, utilizing the AWS Cloud Development Kit (CDK).
-Develop robust and scalable data pipelines using SQL/PySpark/Airflow to efficiently ingest, process, and transform large volumes of data from various sources into a structured format, ensuring data quality and integrity.
-Design and implement an efficient and scalable data warehousing solution on AWS, using appropriate NoSQL/SQL storage and database technologies for structured and unstructured data.
-Automate ETL/ELT processes to streamline data integration from diverse data sources and ensure the platform's reliability and efficiency.
-Create data models to support business intelligence, providing actionable insights and interactive reports to end-users.
-Enable advanced analytics and machine learning capabilities within the platform to derive predictive and prescriptive insights from the data through tools like EMR/SageMaker Notebooks
-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.
-Work closely with data scientists and business intelligence engineers to understand their requirements and collaborate on data-related projects.
-Create comprehensive technical documentation for the platform's architecture, data models, and APIs to facilitate knowledge sharing and maintainability.
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, 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.
Basic qualifications
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
Preferred qualifications
- 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)
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
How we rate this
Data Engineer - Music DISCO, Music DISCO at Amazon rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $146k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where big data was part of your work. What did you do?
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- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
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- List these exact terms on your resume: Big Data, Data Engineering, ETL, Data Modeling, and Data Pipelines. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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