Business Intelligence Engineer, Row Aop

Amazon Amazon · Big Tech · IN, TS, Hyderabad · Business Intelligence

This role focuses on business intelligence and data analysis within Amazon's supply chain. The engineer will analyze large datasets, identify optimization opportunities, build analytical products, and collaborate with stakeholders to drive improvements. While machine learning is mentioned as a tool, the core function is data analysis, metric definition, and building BI solutions, not core AI/ML model development.

What you'd actually do

  1. Analysis of historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
  2. Collaborating with product and software development teams to implement analytics systems and data structures to support large-scale data analysis and delivery of analytical and machine learning models
  3. Mining and manipulating data from database tables, simulation results, and log files
  4. Identifying data needs and driving data quality improvement projects
  5. Understanding the broad range of Amazon’s data resources, which to use, how, and when

Skills

Required

  • Analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • Tableau Desktop, Quicksight or other relevant data visualization software experience
  • data visualization using Tableau, Quicksight, or similar tools
  • data modeling
  • warehousing
  • building ETL pipelines
  • Statistical Analysis packages such as R, SAS and Matlab
  • SQL to pull data from a database or data warehouse
  • Python scripting to process data for modeling
  • SQL (Structured Query Language) to pull data from a database or data warehouse
  • Python scripting to process data for modeling

Nice to have

  • 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.
  • AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • data mining
  • ETL
  • using databases in a business environment with large-scale, complex datasets
  • developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

What the JD emphasized

  • massive data sets
  • analyze massive data sets
  • dive into data to analyze root causes
  • extract or mine information from our existing systems
  • large-scale data analysis
  • Mining and manipulating data
  • large-scale, complex datasets