As the newly implemented Quality Management System (QMS) reaches General Availability globally, we are seeking a highly autonomous Quality Data Analyst to act as the primary engine for system stabilization and data extraction globally. Early-stage systems are notoriously complex and initially unstable; we need a tenacious data specialist who can navigate sparse documentation, extract fragmented data, and build a predictive data pipeline from the ground up. You will be the sole bridge connecting real-time warehouse floor errors directly to our engineering risk documentation, specifically Process Failure Mode and Effects Analysis (PFMEA). By standardizing the data to tell a cohesive story, bypassing the latency of traditional RCCA loops, and defining strict thresholds for risk updates, you will turn operational noise into actionable process improvements and prevent administrative chaos.Top Daily Responsibilities:Investigative System Stabilization: Navigate the newly launched, GA-stage QMS tool to extract, condition, and manage quality data, working through initial system instability and backend API learning curves to create reliable data pipelines.Data Standardization & KPI Alignment: Audit and unify core data streams, working directly with Insights teams to adjust backend tables. You will ensure the correct data is pulled, made visible to users, and aligned with business KPIs so the data tells a cohesive operational story.PFMEA Creation & Implementation: Lead the initial development of Process Failure Mode and Effects Analysis (PFMEA) documentation, establishing the foundational risk matrices from scratch and teaching cross-functional teams how to utilize them as their operational "North Star."Dynamic PFMEA Threshold Management: Once the foundational PFMEAs are built, define and govern strict rules for dynamic updates, ensuring that temporary spikes in shipping errors do not cause these tightly controlled risk matrices to constantly oscillate.Proactive Predictive Analytics: Design early warning systems that feed primarily off raw Issue Management data rather than completed Root Cause and Corrective Action (RCCA) loops, bypassing the standard 5-to-30 day lag time for investigations to surface immediate trends.Operational Feedback Loops: Translate complex quality data into clear mitigation plans. While you do not own the warehouse floor, you will collaborate with cross-functional Operations teams to drive accountability and execute process alignments based on your data findings.