Business Intelligence Engineer, AWS Finance, Analytics and Science Team

Saved job description

AWS is one of Amazon's largest and fastest-growing businesses, serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises leverage information technology.

The AWS Central Economics & Science (ACES) team drives best practices for objectively applying economics and science to decision-making across AWS. Partnering with Finance, Science, and Business teams, ACES identifies, frames, and analyzes complex, ambiguous problems of the highest priority. The ACES Business Intelligence (BI) team supports strategic decision-making across the AWS global organization, delivering data-driven insights that power sales operations and business performance optimization. We are looking for a creative, analytical, and enthusiastic Business Intelligence Engineer to join us.

The ideal candidate is an expert in SQL, ETL, and general data wrangling, with exemplary communication skills. They thrive in ambiguity within a fast-paced, evolving environment and can think big while maintaining careful attention to detail. They are passionate about business intelligence tools and skilled at partnering with stakeholders to answer key business questions.

Key job responsibilities

Work with business customers to gather requirements and deliver complete data analytical solutions

Learn why customers are asking for data and what their underlying questions and business goals are

Own the design, development, and maintenance of ongoing metrics and analyses used to drive key business decisions

Recognize and adopt best practices, including data integrity, accuracy, and reliability, as well as documentation

Leverage AI and emerging innovation in data infrastructure to automate repetitive workflows, accelerate analyses, and unlock new patterns from complex datasets

Drive data democratization throughout the organization, enabling others to self-serve their data needs

Requirements: - 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

- Experience with data visualization using Tableau, Quicksight, or similar tools

- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)

- Experience with scripting language (e.g., Python, Java, or R)