Business Intelligence Engineer II, IES Shopex

Are you analytically sharp and passionate about applying advanced analytics to impact business decisions? Come and be a driving force of the Amazon’s International Emerging Stores Shopping experience team. Amazon IES Shopping team owns the charter for defining the shopping experience across multiple category needs for Amazon's emerging markets. We are a large product organization solving key customer problems through Customer Insights, Tech development and Machine Learning capabilities. We work backwards of emerging customer needs and build solutions to scale these globally. We build adaptive experiences, that adapt to the customer, category and country whom we serve.

Key job responsibilities
The candidate will: - Build scalable solutions and self-serve platforms that will provide data/KPIs to inform business decision making - Investigate data sources across Amazon and expand existing device data infrastructure - Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations that will help grow the business - Develop a thorough understanding of customer behavior and external business drivers to inform decision making - Analyze key insight trends and build models that predict customer behavior, using statistical rigor to simplify and provide thought leadership to device product and marketing groups - Collaborate with finance, marketing, and product management as a leader of ongoing analytical support BASIC

QUALIFICATIONS - Bachelor's degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering). - 5+ years of hands-on experience writing SQL queries. - Experience with building and maintain basic data artifacts (e.g. ETL, data models, queries).Experience with AWS services including S3, Redshift, EMR, Kinesis and RDS. - Experience in working and delivering end-to-end projects independently. - Knowledge of distributed systems as it pertains to data storage and computing. - Experience with one or more data visualization tools (e.g. Tableau, Quicksight, PowerBI) and statistical methods (e.g. t-test, Chi-squared). - 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling - Knowledge of SQL and data warehousing concepts - Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field


PREFERRED QUALIFICATIONS · Inquisitive mindset, with proven problem solving ability, and a passion for big data. · Experience with building multi-dimensional data models to serve as a foundation for future analyses · Experience building/operating highly available, distributed systems of data extraction, ingestion, data modelling and processing of large data sets · Demonstrate proficiency with various approaches in regression, classification, and cluster analysis · Knowledge and experience in data visualization/reporting software (e.g., Tableau). · Advanced SQL / datamining skills and analytical tools (like R / Python / SAS)

About the team
Amazon IES Shopping experience team owns the charter for defining the shopping experience across key country and category needs for Amazon's emerging markets. We are a large product organization solving key customer problems through Customer Insights, Tech development and Machine Learning capabilities. We work backwards of emerging customer needs and build solutions to scale these globally. - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. 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 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

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