Business Intelligence Engineer, Fio Analytics

Amazon Amazon · Big Tech · Bellevue, WA · Business Intelligence

This Business Intelligence Engineer role focuses on building analytics, visualization tools, and processes for the FBA Inventory Optimization organization. The role involves retrieving, integrating, visualizing, and presenting data to improve business decisions, collaborating with research sciences and product teams, and partnering with engineering teams to develop and evaluate Generative AI solutions. The position requires strong analytical abilities, business acumen, and experience with large-scale data analysis and visualization tools.

What you'd actually do

  1. Collaborate with research sciences, product and technology teams in driving step function changes towards influencing seller experience improvements.
  2. Collaborate with senior leadership to implement advanced analytics algorithms and model evaluation framework across Capacity and Inventory Management domains
  3. Own analytics for key domains across inventory optimization services and deliver self-service analytics at scale
  4. Own data governance and stewardship for business critical metrics that influence technology investment decisions
  5. Analyze and visualize transaction data to determine seller behaviors, and output solid analysis with recommendations.

Skills

Required

  • Analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • SQL, ETL or Oracle experience
  • processing large, multi-dimensional datasets from multiple sources experience
  • performing statistical analysis experience
  • developing automated reporting experience
  • data visualization using Tableau, Quicksight, or similar tools
  • data modeling, warehousing and building ETL pipelines
  • Statistical Analysis packages such as R, SAS and Matlab
  • SQL to pull data from a database or data warehouse
  • scripting experience (Python) to process data for modeling

Nice to have

  • AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • data mining
  • ETL
  • using databases in a business environment with large-scale, complex datasets

What the JD emphasized

  • advanced analytics algorithms
  • model evaluation framework
  • Generative AI solutions

Other signals

  • Collaborate with research sciences, product and technology teams
  • implement advanced analytics algorithms and model evaluation framework
  • Partner with product and engineering teams to develop and evaluate Generative AI solutions