Amazon Business Intelligence Engineer JP Seller Services 

Japan 

41545640

Here's the fully reformatted version with consistent punctuation and improved clarity:- Pulling complex data from large scale databases using SQL
- Identifying and developing relevant program metrics
- Automating metrics tracking on Quicksight or Excel
- Running statistical models
Key Responsibilities:- Manage request intake independently and set the right priorities based on organizational needs
- Manage multiple tasks simultaneously and deliver in the most efficient and effective way
- Interact and communicate effectively with stakeholders, including senior leadership from multiple project areas
- Translate complex or ambiguous business problems into analysis requirements
- Extract complex data from large-scale Redshift database using efficient queries
- Develop metrics tracking and automate scheduled report refresh (daily, weekly, monthly and quarterly)
- Innovate solutions that are robust, extensible and scalable
- Ensure accuracy and reliability of data while aligning with globally standardized definitions
- Demonstrate technical expertise (SQL, Python, Statistics, AWS technologies) to efficiently deliver BI solutions
- Effectively communicate with Business Intelligence teams in US/India on technical blockers and requirements
- Make technical trade-offs for long-term/short-term needs- Write documentation outlining analysis details, insights, and recommendationsKey job responsibilities
[Data Visualization][Ad-hoc Data Pull]
Write SQL queries and extract complex data for short/long-term planning and quick decision-making. This requires good judgment in determining what should be supported by the BIE vs. self-managed by the data requester.[Operational Efficiency]
- Drive global initiatives (metrics standardization, dashboard development, infrastructure optimization, development of LLM solutions)
- Innovate local mechanisms (contact reduction, request intake process optimization)A day in the life

- 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