Building and maintaining data pipelines for Trust and Safety is a complex and challenging task that requires a multidisciplinary approach involving expertise in data engineering, data science, and domain-specific knowledge of Trust and Safety issues. The goal is to ensure that the data collected is accurate, reliable, and actionable. This involves designing the pipeline architecture, selecting the appropriate tools and technologies, implementing data quality checks, and continuously monitoring and optimizing the pipeline's performance. From the importance of automation to data integrity and scalability, I've learned the keys to building effective pipelines that tell a complete story. Above all, I've learned that housing sensitive data requires the utmost care and responsibility. I'll share my experiences and insights that can help others build and maintain effective data pipelines for Trust and Safety.