Business Intel Engineer II, DISCO

AI in this role

Build and maintain petabyte-scale big data pipelines and self-service analytics solutions for Amazon Music.

redshifts3sparkscalaairflowjavasql

business-intelligencebig-datadata-modelingetldata-pipelines

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 Business Intelligence 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
Key job responsibilities
• Manage a portfolio of BI solutions (Data Products, Analysis, Dashboards) related to supplier management (performance & risk management, diversity & inclusion etc. ), work with multiple stakeholders and communicate effectively progress and blockers with the project team and sponsors.
• Develop ETL jobs and analytical layers that require in depth knowledge in scripting and AWS technologies (S3, Redshift, Glue, Lambda).
• Implement metadata management and follow core data governance practices
• Develop visualizations that are fast and easy to comprehend.
• Adopt existing best practices or contribute to improving them; solution design, development, validation and documentation practices.

A day in the life
A Business Intelligence Engineer manages requirements from a large group of customers, understands how they operate and is able to build solutions that return the right strategic value back to the organization. Improves the way that customers interact with data and analytics. Works cross functionally, interacting with other tech and non-tech teams globally to align on requirements and solutions. Develops and maintains strong networks and partnerships across organizations, builds trusted relationships. Keeps customers and stakeholders up to date. Innovates in data engineering, analysis, statistics and visualization.

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.

Basic qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience
- Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field, or 2+ years of Amazon RME (BB/3P) Full Time Exempt experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience using SQL (Structured Query Language) to pull data from a database or data warehouse
- Experience using Python scripting to process data for modeling

Preferred qualifications

- Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

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 score this

Business Intel Engineer II, DISCO at Amazon scores 20 out of 100 for how much of the daily work is AI. That makes it AI Level 1 of 4 (Little AI). The level is about AI in the job, not seniority.

Classification

AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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Business IntelligenceBig DataData ModelingETLData PipelinesRedshiftS3Spark

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