Amazon Music is awash in data!
To help make sense of it all, the DISCO (Data, Insights, Science & Optimization) team enables the Consumer Product Tech org to 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 into difficult questions that provide actionable insights.
We also enable measurement, personalization, and experimentation by operating key data programs ranging from attribution pipelines to causal frameworks.
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 a 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 the development, deployment, and operations of big data pipelines.
You'll help build Amazon Music's most important data pipelines and datasets, and expand self-service data knowledge and capabilities through an Amazon Music data university.
Key job responsibilitiesDesign, development, and ongoing operations of scalable, performant data warehouse (Redshift) tables, data pipelines, reports, dashboards, and data transformation strategies to manage a large volume of data.Development of moderately to highly complex data processing jobs using appropriate technologies (e.g., SQL, Python, Spark, AWS Lambda, etc.
)Development of dashboards and reports.Collaborate with internal stakeholders to understand business requirements and provide data-driven solutions.Develop complex SQL queries and optimize performance of SQL queries on large data.Build and manage dashboards, scorecards, and other data visualization using BI tools such as Tableau, Power BI, or AWS Quicksight.Monitor dashboards to ensure the latest data is available, address any technical issues, and enhance existing dashboards based on low-level specifications.Conduct thorough data analysis and troubleshoot data integrity issues, providing gap analysis and business solutions.Actively manage the timeline and deliverables of projects, anticipate risks, and resolve issues.Adopt Business Intelligence best practices in reporting and analysis.Monitor jobs, address any issues, and coordinate for any technical issues.Repeat existing analyses for new scenarios based on existing analyses, pulling datasets using low-level specifications.Monitor pipelines and data quality, address failures and delays, and create and monitor alarms/checks on the pipelines.BASIC QUALIFICATIONS- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with scripting languages (e.g., Python, Java, or R)
- Knowledge of data modeling and data pipeline design
- Experience gathering business requirements, using industry-standard business intelligence tools to extract data, formulate metrics, and build reports
- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, or equivalent quantitative field
- Knowledge of AWS products such as Redshift, Quicksight, and Lambda.
- Excellent verbal/written communication & data presentation skills.
PREFERRED QUALIFICATIONS- Experience in the data/BI space
- Experience with building and maintaining basic data artifacts (e.g., ETL, data models, queries)
- Experience with data-specific programming languages/packages such as R or Python Pandas.
- Experience with AWS solutions such as EC2, DynamoDB, S3, and EMR.
- Knowledge of machine learning techniques and concepts.
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