Business Intelligence Engineer, ISFX

Job description

We are looking for a customer obsessed Business Intelligence Engineer who is comfortable with ambiguity and excited to build intelligence systems that help Account Managers and leaders make better, faster decisions at scale. You should be comfortable working across the full stack of BI and applied ML: writing production SQL, building data pipelines, developing and evaluating ML models (classification, scoring, ensemble methods), designing MCP tool definitions and knowledge schemas, and delivering actionable insights through dashboards and AI powered interfaces.

You will work closely with product, science, and engineering teams

Key job responsibilities

• Design and build MCP server as a centralized knowledge repository, exposing lead context, seller signals, program rules, and historical outcomes to AI agents and tools across Amazon MCP compliant platforms
• Develop and maintain ML driven scoring and prioritization models (intent scoring, conversion prediction, multi signal ensemble models) working alongside the shared Data Scientist, with ownership of feature engineering, model evaluation, and production deployment
• Create, support and continuously improve reports and metrics that support the business operations
• Design and implement data pipelines (SQL, Python, Airflow) that process seller signals, engagement data, and pipeline metrics into actionable intelligence
• Drive automation of repetitive reporting and assignment tasks to scale intelligence delivery across regions
• Convert data into digestible business intelligence and actionable information using tools like QuickSight/Tableau
• Shape and deliver key metrics, reports, and indicators by which our business will assess its performance
• Dive deep into large data sets to answer specific business questions using Excel, SQL and other data manipulation languages
• Work directly with business teams to utilize metrics and analysis to determine improvement opportunities
• Identify process improvement opportunities and drive automation to scale reporting solutions
• Mentor junior analysts and provide guidance on best practices for data analysis and reporting
• Independently manage end-to-end project delivery with minimal supervision