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Description

Transform data into trusted insights that power decisions for millions of Amazon Selling Partners worldwide. Join Spectrum Analytics as we build the data intelligence foundation for one of Amazon's fastest-growing businesses.

The Spectrum Analytics team is implementing data mesh architecture that will enable self-service analytics and AI-powered insights across Selling Partner Services (SPS). As a Business Intelligence Engineer I, you'll build foundational datasets, standardized metrics, and governance frameworks that eliminate data inconsistencies and empower teams to make confident, data-driven decisions. Your SQL expertise and analytical thinking will directly shape how we monitor developer usage, calculate fees, track compliance, and enable emerging GenAI capabilities through Amazon Quick Suite.

Why you'll love this role:
- High-impact greenfield work: Contribute to exciting transformation initiatives as we establish data governance standards and enable self-service analytics across the organization
- Visible business impact: Your BI solutions will directly support critical business decisions affecting millions of Selling Partners and thousands of third-party developers
- Collaborative environment: Partner with Data Engineers, Business Analysts, Software Development Engineers, and Program Managers in a world-class product development team
- Growth opportunities: Work with modern BI tools, AWS technologies, and cloud-based architecture while developing expertise in data governance, quality monitoring, and AI-ready data design
- Fast-paced innovation: Solve diverse data challenges in an environment where your work has highly visible impact on our rapidly growing business

If you're passionate about data quality, love solving analytical problems, and thrive in a collaborative environment where your work enables better business decisions, we want to talk with you.

Key job responsibilities
- Build and maintain small to mid-size BI solutions including datasets, queries, dashboards, and reports that enable data-driven decisions for Selling Partner API teams and stakeholders
- Write high-quality, efficient, testable code in SQL and Scala to extract, transform, and analyze data from distributed systems, ensuring outputs are tested against source data and business logic
- Create standardized, reusable datasets (signals) following data mesh governance principles that eliminate metric inconsistencies and enable self-service analytics across Spectrum
- Develop and maintain ETL processes using SQL and Scala that transform raw domain data into trusted, AI-ready datasets with proper lineage documentation and quality controls
- Build dashboards and visualizations using industry-standard BI tools (QuickSight, Tableau, Excel) that provide actionable insights on developer usage, fee calculations, compliance tracking, and risk monitoring
- Collaborate with Business Analysts, Data Engineers, Software Development Engineers, and business stakeholders to understand requirements, validate data quality, and ensure deliverables align with expectations
- Implement data governance standards including proper classification, Fine-Grained Access Control (FGAC), and standardized naming conventions across all datasets
- Investigate data anomalies, troubleshoot quality issues, and automate manual processes to improve operational efficiency
- Document BI solutions clearly to ensure ease of use, interpretation, and maintainability by team members and downstream consumers
- Partner with Analytics and domain teams to enable GenAI capabilities through Amazon Quick Suite while maintaining robust data security and access controls

A day in the life
You'll start your mornings collaborating with your Analytics teammates—reviewing code with senior engineers, discussing data quality issues flagged overnight, and planning your sprint priorities. Much of your day involves hands-on technical work: writing SQL queries to extract insights from massive datasets, developing Scala ETL scripts to transform raw data into standardized formats, and building dashboards in QuickSight that product managers and operations teams rely on daily.

You'll partner closely with Software Development Engineers to understand how data flows through our systems, work with Data Engineers to optimize pipelines, and meet with business stakeholders to translate their questions into actionable analytics. When a product manager asks "Why did developer adoption drop last week?" or an operations team needs to automate a manual report, you're the one investigating the data, finding the answer, and building solutions that prevent the same question from coming up again.

Your work directly impacts how Selling Partner API teams make decisions. The datasets you create become the foundation for compliance tracking, fee calculations, and developer usage monitoring across Spectrum. You'll see your dashboards referenced in leadership meetings and your standardized metrics adopted by teams across the organization. Beyond the technical work, you'll participate in design reviews, document your solutions so others can build on them, and contribute to our data governance transformation—helping establish the standards that will enable AI-powered analytics across the business.

Some days bring unexpected challenges: a metric suddenly looks wrong and you need to trace through the data lineage to find the issue, or a stakeholder needs urgent analysis for an executive review. Other days, you're heads-down building the next generation of our data infrastructure, knowing that the reusable datasets you create today will save dozens of hours of manual work tomorrow.

About the team
Spectrum Analytics is a lean, high-impact team at the heart of Amazon's Selling Partner Services and Selling Partner API - one of Amazon's fastest-growing businesses serving millions of Sellers, Vendors, and third-party Developers worldwide. Our mission is to enable trusted, impactful business insights through self-service analytics and robust data governance that powers both operational decisions and emerging AI capabilities. We're currently a team of 2 Business Intelligence Engineers, 1 Data Engineer, 1 Technical Support Engineer, and 4 Business Analysts working together to transform how Spectrum leverages data.

In 2026 and beyond, we're executing an ambitious transformation: implementing data mesh governance with clear ownership across domain teams, building an AI-ready data ecosystem that enables conversational analytics through Amazon Quick Suite, and driving adoption of self-service analytics across the organization. We're moving away from being the bottleneck for every data request and instead building the frameworks, standardized signals, and governance infrastructure that empower teams across Spectrum to answer their own questions confidently. This means creating reusable datasets that eliminate metric inconsistencies, establishing data quality standards with automated monitoring, and enabling GenAI tools like Spectrum Assistant to provide natural language access to trusted data.

Our culture values collaboration, technical excellence, and customer obsession. We partner closely with Software Development Engineers, Data Engineers across domain teams, Product Managers, and Business Analysts to understand requirements and deliver solutions that have immediate, visible impact. We celebrate learning—whether that's a senior engineer mentoring on advanced SQL and Scala optimization techniques, or the team collectively solving a complex data lineage challenge. We operate with transparency about our constraints (we're a small team with big goals) and focus relentlessly on high-leverage work that scales: building one standardized dataset that serves ten use cases is better than building ten custom reports. If you're excited about working at the intersection of data engineering, governance, and AI—where your technical work directly shapes how millions of dollars in business decisions get made—you'll thrive here.