Sr Business Intelligence Engineer, GFS FP&A

Amazon Business Intelligence Engineer

Amazon's Global Finance Solutions (GFS) team is a fast-paced, team-focused, dynamic environment and delivering great experiences for our customers is top priority. GFS is seeking a Business Intelligence Engineer to support EU Ops Finance team. As an Amazon Business Intelligence Engineer you will be working in one of the world's largest and most complex data warehouse environments. You should have deep experience in the design, creation, management, and business use of large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be good at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. You should be able to work with business customers in understanding the business requirements and implementing reporting solutions. The person will need to effectively communicate across all levels and be self-motivated to raise the bar on deriving insights from analytics and identify opportunities to delight the customers. Above all you should be passionate about bringing large datasets together to answer business questions and drive change.

Key job responsibilities:

• Own the production and delivery of suite of analytics reports and dashboards used by the organization to make key business decisions.
• Delivery of standardized performance metrics for global customers (vendors) and stakeholders (Amazon Private Brands) providing operational bandwidth to Amazon Private Brands teams to focus on business partnering initiatives.
• Partner with existing BI leader in executing defined roadmap of projects.
• Provide ad-hoc support to Amazon Private Brands and business services for SQL report creation, modification and optimization.
• Debug report issues, unblock workflows and communicate with other teams and stakeholders by providing regular status updates.

Tools used include:

• SQL (Primarily Redshift)
• ETL tools (internal)
• Excel
• Data visualization tools (QuickSight)
• Report scheduling tools (internal)
• Scripting language (e.g., Python, Java, or R)