During October 2025, Chris Reynolds developed a new staging model for the edanalytics/edu_edfi_source repository, focusing on capturing and normalizing student academic honors data. He engineered an ETL pipeline using SQL to flatten complex, nested JSON structures, extracting honor details and descriptors to streamline downstream analytics and improve data consistency. The work included updating project documentation to ensure traceability and governance. By introducing the stg_ef3__student_academic_records__academic_honors model, Chris enabled more reliable analytics and faster reporting. The scope of work was focused and technically sound, demonstrating depth in data engineering and ETL processes, though limited to a single feature within the month.