Worked on the apache/spark repository to deliver a targeted performance optimization for SQL LIKE expressions, specifically improving the handling of multiple '%' wildcards in pattern-matching queries. The approach involved refining query planning and execution logic within Spark SQL, resulting in reduced planning overhead and faster analytics workloads. Leveraging Scala and deep knowledge of Spark internals, the developer implemented a minimal, well-scoped change that addressed the requirements tracked under SPARK-52817. This work demonstrated expertise in data processing and performance tuning, enabling more efficient execution of complex SQL queries and contributing to improved throughput for analytics use cases in Spark environments.