Amazon is a US-based multinational electronic commerce company headquartered in Seattle, Washington. Amazon.com started as an online bookstore, but soon diversified into many other categories, with a vision to be earth’s most customer-centric company & to build a place where people can come to find and discover anything they might want to buy online.
Amazon’s Finance Operations, Accounting & Analysis (FOAA) team is a fast-paced, team-focused, dynamic environment and delivering great experiences for our customers is top priority. FOAA is seeking an experienced Business Intelligence Engineer tot to support our LATAM BIE team.
We are seeking an experienced Business Intelligence Engineer to join our growing team. This person will own the production and delivery of a suite of reports regularly used by the organization to make key business decisions.
The ideal candidate must have superior attention to detail and be driven to provide insightful and timely information to customers. The candidate should have strong communication skills and ability to prioritize effectively to ensure timelines are met. There is always room to make things better, so this candidate should also have the ability to invent and simplify. Lastly, the candidate should have the ability to work effectively with cross-functional teams, and the ability to work in a fast-paced and ever-changing environment.

Key job responsibilities
· Be responsible for taking data analysis and insights capability to the next level; working with data infrastructure to ensure the data is accessible, auditing existing visualization dashboards, and working with stakeholders to recommend and create new reporting/insights
· Converting data into digestible business intelligence and actionable information
· Shaping and delivering key metrics, reports, and indicators by which our business will assess its performance
· Diving deep into large data sets to answer specific business questions using Excel, SQL and other data manipulation languages
· Working directly with business teams to utilize metrics and analysis to determine improvement opportunities Tools used include: 1. SQL (Oracle and Redshift) 2. ETL tools (internal) 3. Excel 4. Tableau 5. Python.