Business Intelligence Engineer, WW Ops Finance S&A

DESCRIPTION

As part of the WW Ops Finance S&A's OPAAT (Operations Finance Planning Automation & Analytics Team), you would be part of a team that is building standardized and scalable financial planning models for WW Operations Finance teams and aim to become intellectual property for Amazon for the next several years to come. Our mission is to reduce manual overhead during planning processes and reduce the time needed to create the financial plan by automating standardized planning solutions. As a BIE in this team, you will get the opportunity to work with leadership across the WW Ops Finance business units to understand their problems and come up with efficient and scalable solutions using AWS ecosystem. Find out more about us in this video: Key job responsibilities
- The BIE will be expected to be proficient in various programming languages like SQL, Python, etc. to propose/utilize the language that solves a problem more efficiently.
- Proficiency in QuickSight or similar BI solution like Tableau, PowerBI etc.
- Having knowledge and experience using AWS big data solutions is preferable as we are a growing team and are making key decisions on the tech infra to support a scalable planning ecosystem
- You would be required to work with stakeholders directly to understand their current processes and propose efficient solutions.
- Good communication skills would be a plus too as being part of OPAAT requires communication across different job families. About the team
OPAAT is a diverse team with currently team members spread across EU & NA. With these new positions, we are working on expanding to India to support our expansion plans to WW Ops. Here in OPAAT, we are all about knowledge sharing across the team and harboring work life balance. We are open to hiring candidates to work out of one of the following locations: Bangalore, KA, IND

BASIC QUALIFICATIONS

- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience writing complex SQL queries