Developed a parallel import feature for the zulip/zulip repository, focusing on optimizing message import performance for large data sets. The work involved implementing concurrent processing of independent message dump files using Python, leveraging backend development and concurrent programming skills. By introducing worker processes and pre-allocating IDs in the update_message_foreign_keys function, the solution enabled reliable parallel handling of message files. Benchmarks on a 17,441-message export demonstrated a 2.4x throughput improvement with four workers on an eight-core machine. This enhancement addressed a longstanding scalability issue, improving both the reliability and efficiency of Zulip’s data import pipeline.