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We are looking for an experienced and enthusiastic Business Intelligence Engineer to join the BI Engineering, Analytics, & Data Science (BAND) team supporting Robotic Storage Tech (RST) programs within Amazon Robotics. In this role, you will bring a strong foundation in statistics to support the introduction of new containerized and workcell robotic products - from early concept through deployment. You will partner closely with cross-functional stakeholders to translate ambiguous questions about new product performance into structured analyses, and author recommendation-focused deliverables that inform program decisions and shape how new robotic systems progress through RST's development lifecycle.

You will design, develop, and maintain dashboards, reports, and other analytics artifacts purpose-built for new product introduction - tracking system maturity, surfacing readiness gaps, and enabling data-driven milestone decisions. You are a collaborative problem-solver who thinks holistically about how new systems evolve from prototype to production and uses data to accelerate that journey.
Key job responsibilities
Statistical Analysis for New Products: Execute foundational statistical methods including hypothesis testing, confidence intervals, design of experiments, and regression analysis to evaluate new containerized and workcell system performance against readiness criteria at each development phase.
Stakeholder Partnership: Collaborate with Data Scientists, Data Engineers, Program Managers, and engineering teams to translate ambiguous new product questions into structured analyses that support milestone decisions

Data Source Development: Identify and onboard data sources from new containerized and workcell systems as they come online, define NPI-relevant metrics, and build data pipelines that enable performance tracking.
Whitepaper & Insights Delivery: Author recommendation-focused whitepapers and deep-dive analyses that inform new product development decisions - including system configuration trade-offs, readiness assessments, and deployment strategy recommendations.
BI Ownership: Design, build, and maintain dashboards and reporting solutions that track new containerized and workcell products through their Alpha, Beta, and General Availability phases, providing visibility into system maturation and operational readiness.

A day in the life
On any given day, you might be helping run a designed experiment to evaluate a configuration change on a new workcell system, building a readiness dashboard for a containerized product approaching its Beta milestone, or authoring a whitepaper that supports a recommendation whether a new system is ready to advance to the next development phase. You will own major components of the BAND team's NPI analytics infrastructure for RST, including contributing to data architecture decisions and delivering reports that track new products from through General Availability.
You will maintain a deep understanding of data lineage across your BI solutions - from the telemetry and event streams generated by new containerized and workcell systems, through metric aggregation processes, to how insights are consumed at milestone reviews and program readiness gates.

You will create and optimize scripts (SQL, Python, R, Shell) to streamline BI processes and select appropriate analytics and visualization tools to meet diverse new product evaluation needs.
Your work will directly influence how new containerized and workcell products move through RST's development pipeline and shape the future of Amazon's robotic storage technology landscape.
About the team
Robotic Storage Tech (RST) invents, designs, and develops transformational storage solutions used in the Amazon Logistic Network.

We will realize the next generation of automated containerized systems, and optimize our existing install base. We are a team of talented engineers, product evangelists, and creators focused on technologies that make inventory pick, stow, and count safer and more efficient for Amazon. We deliver value with our elite robotic technologies because we listen and respond to our many customers, develop robust and reliable solutions, and invest in both our people and our products.