Worked on the apache/spark repository to enhance error handling in Spark SQL, specifically addressing array-type mismatches. Focused on improving the clarity and usefulness of error messages when column types and data types do not align in array columns, this developer implemented a dedicated exception path as outlined in SPARK-49916. Using Scala and leveraging skills in SQL and unit testing, the solution introduced targeted changes to the Spark SQL codebase, enabling more actionable feedback for users encountering data-type inconsistencies. This work improved debuggability and user experience by ensuring that type mismatches in array columns are now surfaced with precise, informative exceptions.