Business Intelligence Engineer III, RISC - Extended Producer Responsibility (EPR)
Are you passionate about transforming complex data challenges into scalable analytics solutions that drive business strategy at Amazon scale? If so, we'd like to talk to you.
As a Business Intelligence Engineer on the WW EPR team, you will own the design, build, and scaling of data infrastructure and BI solutions that power our Worldwide EPR compliance and circularity programs. You will tackle complex, ambiguous problems with high autonomy — building data solutions that inform cross-functional decisions across multiple teams and regions. You will define the team's BI architecture strategy, leverage emerging technologies including Generative AI, and drive innovation in regulatory intelligence, reporting, and cost optimization across global markets.
Key job responsibilities
Data Architecture & BI Solutions
Our Worldwide EPR team owns Amazon's global compliance strategy for Extended Producer Responsibility — ensuring adherence to post-consumer waste regulations across packaging, electronics, batteries, and textiles in all operating regions. We enable circular economy value for Selling Partners, Vendors, and customers by connecting every product sold to verified recovery outcomes with auditable results. We work cross-functionally with Legal, Business, Product, and Data Science/Engineering teams across NA, EU, APAC, and emerging markets to deliver compliance programs at scale.
EPR shifts post-consumer waste management costs from municipalities to producers — requiring all Selling Partners on Amazon's marketplace to register, report product data, pay recycling fees to PROs, and establish take-back systems. This incentivizes environmentally friendly product and packaging design.
EPR is part of the Regulatory Intelligence, Safety and Compliance (RISC) organization, dedicated to protecting Amazon customers from products that are illegal, unsafe, or otherwise prohibited
As a Business Intelligence Engineer on the WW EPR team, you will own the design, build, and scaling of data infrastructure and BI solutions that power our Worldwide EPR compliance and circularity programs. You will tackle complex, ambiguous problems with high autonomy — building data solutions that inform cross-functional decisions across multiple teams and regions. You will define the team's BI architecture strategy, leverage emerging technologies including Generative AI, and drive innovation in regulatory intelligence, reporting, and cost optimization across global markets.
Key job responsibilities
Data Architecture & BI Solutions
- Lead design and delivery of BI solutions spanning EPR compliance, recycling fee analytics, regulatory tracking, and circular economy metrics across worldwide jurisdictions (NA, EU, APAC, emerging markets)
- Define the team's BI architecture strategy — ensuring pipelines, models, and reporting are scalable, extensible, and aligned with organizational standards
- Architect end-to-end solutions: ETL/ELT pipelines, dimensional models, and self-service analytics enabling real-time decision support across geographies
- Harmonize multi-jurisdictional regulatory data — normalizing diverse reporting requirements, fee structures, and compliance timelines across global EPR regimes
- Proactively resolve architecture deficiencies; drive simplification and cross-team integration
- Build automated frameworks that surface cost-saving opportunities within EPR fee structures, eco-modulation incentives, and take-back economics globally
- Integrate EPR cost signals into upstream business decisions — enabling retail and Selling Partner teams to assess cost impact during product selection, design, and pricing
- Develop statistical models and KPI calibration (anomaly detection, regression, confidence intervals) to monitor compliance health and fee trends across WW programs
- Deliver executive-facing narratives, MBR/QBR inputs, and data-driven recommendations for senior leadership
- Leverage GenAI and LLMs to enhance regulatory data extraction, classification, and reporting workflows
- Design AI-augmented solutions (automated regulatory change detection, intelligent fee categorization, natural language querying of compliance datasets)
- Evaluate and implement AI/ML technologies to improve data quality, accelerate insights, and reduce manual overhead
- Set engineering standards, drive code quality, conduct design reviews, and establish operational excellence best practices for the EPR BI function
- Mentor BIE I/II team members; provide technical assessments for promotions and hiring loops
- Influence cross-functional technical decisions by driving BI best practices across partner teams
- Lead the hiring bar for BI roles — recruit, design interview loops, and assess candidates
Our Worldwide EPR team owns Amazon's global compliance strategy for Extended Producer Responsibility — ensuring adherence to post-consumer waste regulations across packaging, electronics, batteries, and textiles in all operating regions. We enable circular economy value for Selling Partners, Vendors, and customers by connecting every product sold to verified recovery outcomes with auditable results. We work cross-functionally with Legal, Business, Product, and Data Science/Engineering teams across NA, EU, APAC, and emerging markets to deliver compliance programs at scale.
EPR shifts post-consumer waste management costs from municipalities to producers — requiring all Selling Partners on Amazon's marketplace to register, report product data, pay recycling fees to PROs, and establish take-back systems. This incentivizes environmentally friendly product and packaging design.
EPR is part of the Regulatory Intelligence, Safety and Compliance (RISC) organization, dedicated to protecting Amazon customers from products that are illegal, unsafe, or otherwise prohibited
Basic Qualifications
- 10+ years of professional or military experience
- 5+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience
- 5+ years of SQL experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience working directly with business stakeholders to translate between data and business needs
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval, data science, machine learning and data mining
Preferred Qualifications
- Master's degree in statistics, data science, or an equivalent quantitative field
- Knowledge of data warehousing and data modeling
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc.