Are you excited about uncovering actionable insights to improve delivery experience? Do you get excited about operating in an ambiguous and fast-moving environment? Are you looking for an opportunity to define analytics roadmap, work with cross-functional teams, experiment with AWS tech solutions, and build decision-driven analytics solutions for work that is critical to Amazon's continued ability to deliver smiles in communities?

We are looking for an innovative and highly-motivated Business Intelligence Engineer (BIE) who can think holistically about problems to understand how systems work together to identify and execute both tactical and strategic projects. You will work closely with engineering teams, product managers, program managers, and org leaders to deliver end-to-end data solutions aimed at continuously enhancing overall delivery operations and Trans Execution BR performance.

Key job responsibilities

• You will have an opportunity to lead medium to large-scale projects along with owning multiple domains within the team and contributing to the analytics roadmap. You will be instrumental in transforming manual processes into automated, scalable solutions that support scheduling, capacity management, and operational excellence across all delivery channels in Brazil.
• Earn the trust of your customers and stakeholders by continuing to constantly obsess over their business use cases and data needs, and helping them solve their problems by leveraging technology.
• Work closely with business stakeholders and leadership team to review roadmap and contributing to business strategy and how they can leverage
• Manage and execute entire projects from start to finish including stakeholder management, data gathering and manipulation, modeling, problem solving, and communication of insights and recommendations.
• Extract, transform, and load data from many data sources using SQL, Scripting and other ETL tools.
• Design, build, and maintain automated reporting, dashboards, and ongoing analysis to enable data driven decisions across our team and with partner teams.
• Report key insight trends using statistical rigor to simplify and inform the larger team of noteworthy trends that impact the business.
• Retrieve and analyze data using a broad set of Amazon’s data technologies (ex. Redshift, AWS S3, Amazon Internal Platforms/Solutions) and resources, knowing how, when, and which to use.

About the team
The Trans Execution BR team at AMZL Brazil is a newly established, high-impact function responsible for the end-to-end management of Brazil's delivery network. Our scope encompasses capacity planning, demand forecasting, scheduling and route optimization, and risk management across all delivery channels. We are building this team from the ground up, with a mission to transform a highly manual, Excel-driven process into a scalable, automated, and data-driven operation that serves the full spectrum of Amazon's delivery models in Brazil.
We operate in a fast-paced, ambiguous environment where operational rigor and innovative thinking go hand in hand. We are part of a global community of Trans Execution teams, with counterparts in Japan, India, and other geographies, and we actively collaborate across borders to share best practices and co-develop technology solutions. Our team is growing rapidly, and we are looking for people who are excited to build something new, solve hard problems, and make a measurable impact on Amazon's delivery network in Brazil.

Basic Qualifications

• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, Quick Sight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
• Experience with scripting language (e.g., Python, Java, or R)
• Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
• Speak, write, and read fluently in English

Preferred Qualifications

• Master's degree, or Advanced technical degree
• Knowledge of data modeling and data pipeline design
• Experience with statistical analysis, co-relation analysis

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