Key job responsibilities - Design, develop, and maintain scalable analytical solutions, dashboards, and data pipelines using Amazon QuickSight, SQL, and AWS services to track forecast performance across Topline, Inventory, and Capacity planning - ensuring solutions are extensible, well-architected, and easy for others to maintain - Partner with scientists, engineers, product managers, and cross-functional stakeholders to gather requirements, prioritize initiatives, and deliver data solutions that drive to root cause - Build and optimize data models, ETL processes, and automated reporting mechanisms that enable data-driven decision making across the organization - Identify and implement opportunities to integrate generative AI into analytical tools and processes, accelerating insight generation and automating reporting workflows - Conduct deep-dive analyses to identify trends, patterns, and opportunities for improvement, leading the analytics strategy for complex and ambiguous business questions independently - Identify and mitigate data quality issues, dependencies, and bottlenecks; escalate and drive resolution as needed - Take the lead on large projects from start to finish - developing project plans, tracking milestones, and communicating findings effectively to management audiences - Influence the team's analytics strategy and drive best practices in data modeling, metric definitions, and code quality - continuously improving processes and tools - Mentor and develop other team members; participate in hiring and technical assessments A day in the life LTPF BI Engineers focus on how our customers use our forecasts and plans, and ensuring it's as easy as possible to access and understand them. Basic Qualifications - 5+ years of SQL experience - 5+ years of processing large, multi-dimensional datasets from multiple sources experience - 5+ years of developing automated reporting experience - 5+ years of performing statistical analysis experience - Experience programming to extract, transform and clean large (multi-TB) data sets - Experience with theory and practice of design of experiments and statistical analysis of results - Experience with AWS technologies - Experience in scripting for automation (e.g.