Developed Near-Real-Time indexing pipeline using Python and Elasticsearch, reducing end-to-end data preprocessing and indexing time from 27 to 7 hours.
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Led the creation of an indexing pipeline to support new file types (PDF, Microsoft Word, and PPT) with Python and Elasticsearch.
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Implemented an index validation tooling and alerting system with Python and Prometheus, ensuring data integrity and enabling custom configurations for different customers.
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Designed and built a Python-based web tool using Django to visualize search index building history and document change logs, enhancing collaboration among non-engineering colleagues.
Developed 6 automated pipelines with Hadoop, Scala, and SQL for sampling job data and generating CSV files for human annotation in LinkedIn's search and recommendation products.
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Designed and built an automated ML model pre-ramp regression test system with Java and JUnit. Helped avoid ambiguities in manual testing and saved days of manual time.
