Business Intelligence Engineer, ProdOps OAT, Leo

Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity.

Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Role Overview

As a Business Intelligence Engineer (BIE), you will implement and maintain effective analytics solutions that drive data-informed decisions to streamline the production of Leo's satellite technology. You will focus on creating efficient, maintainable, and well-documented processes for data analysis and reporting.

As a BIE within Leo ProdOps, you will tackle complex data challenges and translate them into clear, actionable insights for the business. You are a customer-obsessed problem-solver who will build effective partnerships across Leo's ecosystem, including hardware, software, supply chain, manufacturing, launch, facilities, transportation, and finance teams. Your ability to invent and simplify processes will be key to solving day-to-day data needs. You will use your communication skills to articulate data concepts clearly and collaborate with diverse technical and non-technical stakeholders to deliver results. You will contribute to the team's engineering excellence by implementing best practices and proactively seeking opportunities to learn and share knowledge.



Key job responsibilities
- Collaborate with cross-functional and cross-organizational teams to understand business needs and implement data-driven solutions that enable better decision making
- Define and track key metrics and performance indicators to monitor performance and drives continuous improvement across Leos's operations.
- Execute analytical approaches to uncover new insights and share recommendations that improve productivity
- Design and build robust, self-service reporting solutions that scale across the organization
- Write complex, performant SQL queries and develop efficient data pipelines to support both recurring and ad-hoc analytical needs
- Build and maintain data infrastructure in collaboration with BIEs/DEs, focusing on improving data quality and availability
- Communicate analytical findings and methodology to diverse stakeholders through clear documentation and presentations
- Lead technical initiatives and actively share knowledge with team members, supporting analytics best practices
- Maintain awareness of AI/ML advancements (especially around LLMs and GenAI) and propose new technologies for team consideration

A day in the life
This role will be highly collaborative, requiring partnerships with cross-functional leaders to drive positive results. You will tackle challenging, novel business problems every day and have the opportunity to work with multiple technical teams of Leo. You should be comfortable with a high degree of ambiguity and relish the idea of solving problems that haven't been solved at scale before. Along the way, we guarantee that you will learn a lot, have fun and make a positive impact on millions of people.

About the team
The Operations Analytics Team (OAT) was established to develop end-to-end analytics products across Leo Production Operations (ProdOps). This includes both tools and insights for ProdOps leadership and functional teams. OAT products are leveraged as the single-source-of-truth for insights and metrics that production teams rely on to drive performance. OAT works in parallel with the Leo Production PMO to coordinate actions and release analytics products across all Leo teams.

Basic Qualifications

- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 3+ years of BIE or similar role experience with writing complex, highly-optimized SQL queries across large datasets
- 3+ years experience with data visualization using Tableau, Quick Suite, Grafana, or similar tools
- 3+ years experience with data modeling, warehousing and building ETL pipelines
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience in Statistical Analysis packages such as R, SAS and Matlab

Preferred Qualifications

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data minin