Business Intel Engineer, re:Cycle Reverse Logistics

re:Cycle Reverse Logistics is an electronics processing, reuse, and recycling company that works to extend the life of used electronic equipment through reuse, repair, and recycling. We are a stand-alone company within the Amazon corporate family that provides services to other Amazon companies. We specialize in the handling of valuable electronic equipment that was originally used in data centers. Come join our team and be a part of history as we deliver results for the largest cloud services company on Earth!

re:Cycle Reverse Logistics is looking for a talented and driven Business Intelligence Engineer (BIE) to build and scale the data infrastructure that powers our planning and operations functions. Our mission is to manage and scale information technology asset disposition (ITAD) services for used electronics and electronic equipment (UEEE) through secure and environmentally sustainable practices supporting asset recovery, reuse, recycling, and other circular economy initiatives.

In this role, you will be responsible for designing and building the data pipelines, tables, and automated reporting systems that enable our Planning, Operations, and Finance teams to make faster, more accurate decisions. You will develop and maintain ETL processes that consolidate data from across the RRL network — spanning inbound receipts, facility processing, parts disposition, and outbound logistics — into reliable, queryable data models. You will create and maintain interactive dashboards and self-service analytics tools that track KPIs, support monthly S&OP processes, and provide real-time visibility into capacity, throughput, and operational performance across our global facilities. This role requires deep technical expertise in SQL, data modeling, and pipeline architecture, combined with the ability to understand business context and translate operational needs into scalable data solutions. You will work closely with the reporting and analytics team, planning analysts, operations leaders, and product management to ensure the right data is available at the right time to drive accountability, process improvements, and strategic decision-making.


Key job responsibilities
- Design, build, and maintain scalable ETL pipelines and data models that consolidate planning, operations, and financial data across the RRL network into a unified and reliable data architecture
- Develop and maintain automated reporting solutions and interactive dashboards (QuickSight or similar) that support daily operations, monthly S&OP, capacity planning, and executive-level performance reviews
- Build and optimize data tables and warehouse structures that enable accurate volume projections across the full lifecycle — inbound receipts, facility processing throughput, parts testing and sparing, and outbound disposition
- Partner with planning analysts and product management to translate business requirements into technical data solutions, ensuring tooling and reporting meet evolving operational needs
- Create and maintain data pipelines that feed planning models, forecasting tools, and capacity planning systems used across global facilities
- Develop self-service analytics capabilities that empower operations, planning, and finance teams to independently access and analyze data without ad hoc engineering support
- Establish data quality frameworks, monitoring, and validation processes to ensure accuracy and reliability of reporting across all downstream consumers
- Support cross-functional collaboration by providing analytic roll-ups, data extracts, and custom reporting for Operations, Commercial, Program Management, and Finance leadership
- Document data architecture, pipeline logic, and reporting methodologies to ensure institutional knowledge and enable team scalability
- Identify opportunities to automate manual reporting processes and reduce time-to-insight for key business stakeholders

Basic Qualifications

- Bachelor's degree or equivalent in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
- 3+ years of using SQL to extract and manipulate data experience
- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
- 3+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience

Preferred Qualifications

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience building and managing financial models for business forecasting and problem solving, or experience delivering forecasting, budgeting, and variance analysis, and data interpretation of results